Research ArticleRisk Evaluation on UHV Power Transmission ConstructionProject Based on AHP and FCE Method

Huiru Zhao and Sen Guo

School of Economics and Management North China Electric Power University Beijing 102206 China

Correspondence should be addressed to Sen Guo guosen324163com

Received 31 October 2013 Revised 24 December 2013 Accepted 25 December 2013 Published 16 January 2014

Academic Editor Ching-Ter Chang

Copyright copy 2014 H Zhao and S GuoThis is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

Ultra high voltage (UHV) power transmission construction project is a high-tech power grid construction project which facesmany risks and uncertainty Identifying the risk of UHV power transmission construction project can help mitigate the risk lossand promote the smooth construction The risk evaluation on ldquoZhejiang-Fuzhourdquo UHV power transmission construction projectwas performed based on analytic hierarchy process (AHP) and fuzzy comprehensive evaluation (FCE) method in this paper Afterthe risk evaluation index system was built the AHP was used to determine the weights of risk indicators and the FCE methodwas to perform the risk evaluationThe evaluation result shows that (1) ldquoZhejiang-Fuzhourdquo UHV power transmission constructionproject has moderate risk which indicates the occurrence probability of project risk is medium and the risk occurrence will causegeneral loss for project (2) ldquosociety riskrdquo has the highest level and the next is ldquopolicy and law riskrdquo ldquotechnique riskrdquo ldquonaturalenvironmental riskrdquo and ldquoManagement riskrdquo respectively and it should keep main eye on the social risk policy and law risk andtechnique risk Finally according to the risk evaluation result the specific risk control recommendations were proposed for thesmooth construction of this project

1 Introduction

The energy resource distribution and energy consumptionpattern in China are inconsistentThe regions with abundantenergy resources are usually far from the economy-developedregionswith large energy consumption [1] Facing the currentsituations such as the coal-dominated energy structurereverse distribution between energy production and con-sumption and the rapid development of renewable energyindustry China needs to build the strong power grid to realizethe optimal configuration of different energy resources inlarger area and then the electricity demands of the socialeconomic development as well as peoplersquos livelihood can bemet The current 500 kV power grid in China is limitedfor the long-distance and large-volume electricity powertransmission and it is difficult to efficiently transmit theelectricity power generated by the western hydropower baseand the north coal-power base to the central and easternregions of China Therefore to advance the harmoniousdevelopment of both the economy and society building theultra high voltage (UHV)power transmission systemwith the

transmission capacity of long distance high capacity and lowloss is of great importance which can promote the intensi-fication development of large-scale coal-power hydropowerand nuclear-power generation bases optimize the energyproduction and consumption pattern and enhance the safetyand reliability of Chinarsquos power grid [2]

In China the UHV power transmission constructionprojects are dispersed in many areas which will face manyissues such as harsh natural environment many participa-tion partners a lot of works high above the ground andcomplicated local relationshipTheUHVpower transmissionconstruction project is the combination of technologicalinnovation and engineering construction which has thecharacteristics of high technological requirement heavyworkload and significant demonstration effect Comparedwith the conventional construction projects the UHV powertransmission construction project faces more challenges andrisks Therefore building the risk evaluation index systemand evaluating the comprehensive risk of UHV power trans-mission construction project are quite necessary To thebest of our knowledge many researchers who study the

Hindawi Publishing CorporationMathematical Problems in EngineeringVolume 2014 Article ID 687568 14 pageshttpdxdoiorg1011552014687568

2 Mathematical Problems in Engineering

power project issues put their attentions on power generationprojects [3ndash7] and some researchers evaluate the risk ofultra-deep scientific drilling project [8] undergroundminingproject [9] PPP waste-to-energy incineration projects [10]intelligent software project [11] and so on However it is veryregretful to find that the risk of UHV power transmissionconstruction project has rarely been studied The risk eval-uation on UHV power transmission construction project canidentify the risk of project and provide some suggestions forthe risk management and control

ldquoZhejiang-Fuzhourdquo UHV power transmission construc-tion project is a key power grid project invested by theState Grid Corporation of China (SGCC) which plays animportant role in keeping the power network operating insafe and stable condition promoting the efficient utilizationof Chinarsquos energy and advancing the regional economicdevelopment The risk of ldquoZhejiang-Fuzhourdquo UHV powertransmission construction project was evaluated by usinganalytic hierarchy process (AHP) and fuzzy comprehensiveevaluation (FCE) method in this paper (the reason whyweselected AHP and FCE method to perform the riskevaluation will be discussed in Section 4) The evaluationresult can identify the risk level of this project point out thekey risk criteria that need to be paid more attention andprovide the basis for the recommendations of controlling theproject risk

The paper is organized as follows Section 2 provides anoverview of ldquoZhejiang-Fuzhourdquo UHV power transmissionconstruction project which lays the foundation for buildingthe risk evaluation index system Section 3 identifies therisk index of ldquoZhejiang-Fuzhourdquo UHV power transmissionconstruction project by using Delphi method and buildsthe risk evaluation index system The risk evaluation ofldquoZhejiang-Fuzhourdquo UHV power transmission constructionproject based on AHP and FCE method is performed inSection 4 Specific risk control recommendations are pro-posed in Section 5 Section 6 concludes this paper

2 Overview of lsquolsquoZhejiang-Fuzhoursquorsquo UHVPower Transmission Construction Project

21 Project Profile ldquoZhejiang-Fuzhourdquo UHV power trans-mission construction project is invested by the SGCC whichconnects the 1000 kV substation located in the north ofZhejiang province and 1000 kV substation located in Fuzhoucity (the provincial capital of Fujian) just as shown inFigure 1 This project will build three new UHV transformersubstations and two 603 km-length AC transmission linesThe static and dynamic investments of this project amountto 20716 and 21336 billion Yuan respectively The capitalrequired in this project is composed of own fund and bankloan which accounts for 20 and 80 respectively As thelegal representative the SGCC is responsible for this projectrsquosconstruction operation and repayment of loan principal andinterest ldquoZhejiang-Fuzhourdquo UHV power transmission con-struction project is very urgent in terms of project durationwhich plans to be put into operation during the ldquo12th Five-Year Planrdquo period If this project can be constructed and put

transmission line

substation1000 kV

1000 kV

Figure 1 Geographical distribution of ldquoZhejiang-Fuzhourdquo UHVpower transmission construction project

into operation as planned the power transmission bottleneckof East China Power System can be mitigated and the safeand reliable operation of East China Power System can alsobe enhanced Meanwhile this project will make preparationfor the future construction of UHV power grid

This project is an important part of building the strongpower grid of East China Power System and it is alsoan ACDC UHV power receiving platform for Zhejiangand Fujian power grid This project plays a crucial role insupporting the safe and stable operation of power grid withUHVDC accessing the Zhejiang power grid Meanwhile itprovides a main power exchange channel from Zhejiang toFujian More importantly this construction project could fillthe electricity gap of Zhejiang power grid and send out thepower surplus of Fujian power grid during the ldquo12th Five-YearPlanrdquo period

22 Project Characteristics ldquoZhejiang-Fuzhourdquo UHV powertransmission construction project has many special charac-teristics just as follows

221 Tight Time According to the milestone plan the UHVtransformer substation project was commenced at the end of2012 while the transmission line excavation was started inMarch 2013 and planned to be completed in December 2014Due to the delaying of approval from the National EnergyAdministration and the relevant preresearching reports it isimpossible to reach the target of being approved at the end ofthis year which will affect the subsequent project tasks suchas construction drawing design project bidding and contractsigning If the operation schedule remains unchanged theeffective project duration will be significantly shortened

Mathematical Problems in Engineering 3

222 Heavy Task For this project the land acquisitionformality is very complicated with heavy workload and longprocess At some substation sites some farms and graves needto be relocated Meanwhile when the project workers carriedout drilling and performed land acquisition some villagersobstructed them by using the negative effect of electromag-netic radiation as an excuse Moreover the transmission linewould pass through the areas with widely distributedmineralresources and numerous nature reserves which will bring anegative impact on the project construction The local folkcustom is another big concern What is more the majorequipment and materials for substationsrsquo and transmissionlinesrsquo constructions need take long time and huge workloadto manufacture which is quite likely to go beyond theproduction capacity of domestic equipment manufacturingenterprises

223 Difficult Construction The construction of ldquoZhejiang-Fuzhourdquo UHV power transmission construction project willface many difficulties The substation project will encounterlarge earthwork cutting-filling and massive piling construc-tionsThe installed equipment is miscellaneous and both theinstallation and testing standards are strict The equipmenttransportation is difficult and many roads and bridges needto be broadened and reinforced The geological feature andfoundation type along the project line are quite complex andthe required construction technique level is highThe terrainalong the project line is undulate with high altitude so it isdifficult to transport the tower construction materials Theproject line crosses a large number of roads and rivers whichmakes the construction more complicated

224 Complicated Environment There are many tasksof ldquoZhejiang-Fuzhourdquo UHV power transmission projectincluding project approval feasibility study design start andcompleted acceptance and so on All these tasks face differentexternal environments Meanwhile with the market openingand economic development in China the numbers of policiesand laws affecting the project construction are increasingIn China the society is relatively stable and harmoniousbut it is undeniable that there are still some problems andcontradictions in some social areas some of which are veryserious that may adversely affect and even hinder this projectconstruction if not handled properly What is more thisproject locates along the southeast coast where the geologicalconditions are quite complex with a lot of mountains andhills

3 Building the Risk Evaluation Index System

Risk index identification is a basis for building the risk eval-uation index system which is the beginning of UHV powertransmission construction project management The goal ofrisk index identification is to identify themost important riskindex Commonly the risk index could be identified by usingDelphimethodwhich relies on the perceptual knowledge andexperience of a panel of experts

Analyze the project characteristics and collect the relevant literatures and

documents

Select the experts in the field of power grid construction and project managers

Design and distribute the questionnaire

Calculate and classify the questionnaire results

Do all the experts hold the same opinion

No

Yes

Obtain the risk factors and build the risk evaluation index system

Figure 2 The procedure of risk index identification

For ldquoZhejiang-Fuzhourdquo UHV power transmission con-struction project based on the project characteristics as wellas the relevant literatures and documents the risk index ofUHV power transmission construction project is identifiedby using Delphi method The risk index identification proce-dure is shown in Figure 2

The questionnaire regarding the risk of ldquoZhejiang-Fuzhourdquo UHV power transmission construction projectincludesmore than 60 risk indicatorsThe experts and projectmanagers conducted the questionnaire survey based on theirknowledge and experience By calculating the questionnaireresults 39 main risk indicators are selected for the ldquoZhejiang-Fuzhourdquo UHV power transmission construction projectwhich are called the second-level risk index According to

4 Mathematical Problems in Engineering

the characteristics of selected risk indicators and the expertadvices these 39 risk indicators are divided into ldquopolicyand law riskrdquo ldquomanagement riskrdquo ldquotechnology riskrdquo ldquonaturalenvironment riskrdquo and ldquosociety riskrdquo which are called thefirst-level risk criteria Therefore the risk evaluation indexsystem of ldquoZhejiang-Fuzhourdquo UHV power transmission con-struction project is built just as shown in Figure 3 FromFigure 3 we can see that the risk evaluation index systemcontains 5 first-level risk criteria and 39 second-level riskindicators

4 Risk Evaluation on lsquolsquoZhejiang-FuzhoursquorsquoUHV Power Transmission ConstructionProject Based on AHP and FCM

Therisk evaluation on ldquoZhejiang-FuzhourdquoUHVpower trans-mission construction project targets the safe and smoothoperation of project Risk evaluation is the combinationof qualitative evaluation and quantitative evaluation Withregard to the UHV power transmission construction projectit is very hard to describe some risk factors with quantitativemethods precisely moreover some risk factors are valuedby experts with certain ambiguity Therefore the risk ofUHV power transmission construction project needs to beevaluated by using a certain fuzzy evaluationmethod In viewof this characteristic the fuzzy comprehensive evaluation(FCE) method is employed in this paper

Determining the weight of each risk indicator is a difficultbut crucial work when using FCEmethod to evaluate the riskof UHV power transmission construction project Whetherthe index weight value is reasonable or not is directly relatedto the reliability of risk evaluation result With regard tothe risk evaluation of UHV power transmission constructionproject it is a multiobjective issue that needs to considermany uncertain factors such as policy society and envi-ronment and so on meanwhile it also has a hierarchicalstructure Therefore the AHP method which can effectivelydeal with the issue with a hierarchical structure and considerthe wisdom and experience of expert to overcome theuncertain factors is selected to determine the risk indexweight

The AHP is a multiobjective decision-making tool com-bining qualitative and quantitative analysis [12] Its principleis as follows firstly divide the research issue into a hierarchi-cal structure based on the interrelationship and membershipbetween indicators secondly compare the importance ofeach indicator within the same layer with regard to theupper layer depending on the experience or intuition ofexperts thirdly obtain the importance of each indicatorwith regard to the final object through the hierarchicalstructure and use the consistency test to justify the resultaccuracy [13 14] The risk evaluation index system of UHVpower transmission construction project is such a systemthat contains a multilevel hierarchical structure and existscorrelation among indicators Therefore it is suitable to useAHP method to determine the weights of risk indicators

FCE method intended to quantify the vague factorswhich are difficult to quantify based on fuzzy mathematical

Table 1 The meaning of different risk types

Risk types Meaning

High risk The occurrence probability of project risk is greatand the risk occurrence will cause huge loss

Moderate riskThe occurrence probability of project risk ismedium and the risk occurrence will causegeneral loss

Low risk The occurrence probability of project risk is lowand the risk occurrence will cause small loss

method is a fuzzy bottom-up multicriteria decision making(MCDM) method [15 16] As a specific application of fuzzymathematics method FCE method was proposed by theChinese scholar P Z Wang Considering the various factorsassociated with the evaluation system the FCE method usesthe fuzzy linear transformation principle and maximummembership degree principle to quantify the fuzzy indicators

The framework of risk evaluation on ldquoZhejiang-FuzhourdquoUHV power transmission construction project based onAHP and FCMmethod is shown in Figure 4

The specific calculation steps for the risk evaluation onldquoZhejiang-Fuzhourdquo UHV power transmission constructionproject based on AHP and FCE method are as follows

41 Step 1 Building the Risk Evaluation Index System Theriskevaluation index system of ldquoZhejiang-Fuzhourdquo UHV powertransmission construction project has been built in Section 3just as shown in Figure 3

42 Step 2 Determine the Evaluated Object and EvaluationIndex Set For the evaluated object F the evaluation index set119862 = 119862

119894 (119894 = 1 2 119899) is an entiretywith intrinsic structure

composing of the indicators that represent the characteristicsof the evaluated object F

In this paper the evaluated object F is the risk ofldquoZhejiang-Fuzhourdquo UHV power transmission constructionproject The evaluation index set is composed of 39 riskindicators namely 119862 = 119862

119894 (119894 = 1 2 39)

43 Step 3 Give the Remark Set According to the evaluationstandard and grade the remark set V = [V

1 V2 V

119898] can

be made based on the opinions of experts and engineersconsidering the qualitative index and quantitative indextogether The remark set V is composed of different riskgrades and 119898 in the remark set V represents the number ofrisk grades

In this paper according to the characteristics ofldquoZhejiang-Fuzhourdquo UHV power transmission constructionproject and the expertise suggestion in the field of powergrid construction project the evaluated risk is divided intothree types namely ldquohigh riskrdquo ldquomoderate riskrdquo and ldquolowriskrdquo the meanings of which are listed in Table 1 Thus theremark set V can be made namely V = [V

1 V2 V3]

Mathematical Problems in Engineering 5

ldquoZhejiang-Fuzhourdquo

UHV power transmission construction

project

Policy and law risk

Technology risk

Society risk

Natural environmentrisk

Management risk

Project approval policy risk

Loan policy risk

Environmental protection law risk

Unsound traffic law risk

Adjustment risk on energy development strategyand electric planning policyLand requisition and logging policy risk

Quality management risk

Security management riskGoods and material management risk

Contract management risk

Bidding management risk

Project budget risk

Project design risk

Feasibility research risk

Other department coordination risk

Operation preparation riskCompletion inspection and approval risk

Debugging riskImmature contractor risk

Supervision risk

Investment risk

Schedule risk

Substation construction risk

Technical immature risk

Depopulated zone construction risk

Mountain material transportation risk

Tower construction risk

Important line crossing risk

Equipment installation risk

Grounding project resistance reduction risk

Large equipment transportation risk

Social and public opinion risk

Possible social risk due to immature regime

Life security concern risk

Maladjustment risk to the living environment changes

Possible ecological damage risk

Land requisition removing and crop compensation risk

Natural disaster risk

Adverse geological condition risk

Figure 3 The risk evaluation index system of ldquoZhejiang-Fuzhourdquo UHV power transmission construction project

6 Mathematical Problems in Engineering

Construct the hierarchical structure model

Construct the judgment matrixes

Determine the weight vector of risk index

Consistency test

Satisfied

Determine the evaluated object and evaluation index set

Give the remark set

Determine the index weight

Calculate the fuzzy relation matrix

Make fuzzy composition

Rate and conclude the grade level

AHP method to determine index weight

Nonsatisfied

Build the risk evaluation index system

Figure 4 The framework of risk evaluation

44 Step 4Determine the IndexWeight byUsingAHPMethodIn this paper the AHP method is employed to determinethe index weight After building the evaluation index systemthe local weight 119882

119871= 1199081198711

1199081198712

119908119871119899

and global weight119882119866

= 1199081198661

1199081198662

119908119866119899

of indicators in index layer andthe weight119882 = 119908

1 1199082 119908

ℎ of indicators in criteria layer

can be calculated where sum119899

119894=1119908119866119894

= 1 sumℎ119894=1

119908119894= 1 0 le 119908

119866119894

119908119894le 1

441 Substep 1 Construct the Hierarchical Structure ModelAccording to the overall goal and characteristics of MCDMproblem the complex determination of index weight isdecomposed and framed as a bottom-up hierarchical struc-ture which includes the goal layer criteria layer and indexlayer just as shown in Figure 5

In this paper the risk evaluation index system contains5 first-level risk criteria and 39 second-level risk indicatorsSuppose 119880 = 119880

1 1198802 1198803 1198804 1198805 = policy and law risk

management risk technology risk natural environment risksociety risks 119862 = 119862

1 1198622 119862

39 = project approval

policy risk adjustment risk on energy development strategyand electric planning policy land requisition and loggingpolicy risk social and public opinion risk The bottom-up hierarchical structure of risk evaluation of ldquoZhejiang-Fuzhourdquo UHV power transmission construction project isshown in Figure 6

Goal

Index

Criteria middot middot middot middot middot middot

middot middot middot middot middot middot middot middot middot

middot middot middot middot middot middot middot middot middot

Figure 5 The hierarchical structure of AHP for determining theindex weights

442 Substep 2 Construct the Judgment Matrixes The AHPuses the pairwise comparison method to construct thejudgmentmatrixes for both criteria layer and index layerThepairwise comparison is performed by using a nine-point scalewhich can convert human preference into quantitative valuejust as shown in Table 2

According to the analysis shown in Table 2 it shows that119886119894119895

gt 0 119886119894119894= 1 119886

119895119894= 1119886119894119895

In this paper after recognizing the judgments and opin-ions of experts and engineers related to UHV power trans-mission construction project according to the questionnaireresult the judgment matrixes of criteria layer and index layerby using the nine-point scale pair-wise comparison methodare constructed and the results are shown in Tables 3 4 5 67 and 8

Mathematical Problems in Engineering 7

Criteria

Risk evaluation of ldquoZhejiang-Fuzhourdquo UHV power transmission construction project

Policy and law risk Technology risk

Index

Management risk

Quality management risk

Security management risk

Goods and material management risk

Contract management risk

Bidding management risk

Project budget risk

Project design risk

Feasibility research risk

Other department coordination risk

Operation preparation risk

Completion inspection and approval risk

Debugging risk

Immature contractor risk

Supervision risk

Investment risk

Schedule risk

Project approval policy risk

Loan policy risk

Environmental protection law risk

Unsound traffic law risk

Adjustment risk on energy development strategy and electric

planning policy

Land requisition and logging policy risk

Substation construction risk

Technical immature risk

Depopulated zone construction risk

Mountain material transportation risk

Tower construction risk

Important line crossing risk

Equipment installation risk

Grounding projectresistance reduction risk

Large equipmenttransportation risk

Natural environment risk

Natural disaster

risk

Adverse geological condition

risk

Possible social risk due to immature

regime

Life security concern risk

Maladjustment risk to the living

environment changes

Possible ecological damage risk

Land requisition removing and crop compensation risk

Social and public opinion risk

Society risk

Goal

(C1)

(C2)

(C3)

(C4)

(C5)

(C6)

(C7)

(C8)

(C9)

(C10)

(C11)

(C12)

(C13)

(C14)

(C15)

(C16)

(C17)

(C18)

(C19)

(C20)

(C21)

(C22)

(C23)

(C24)

(C25)

(C26)

(C27)

(C28)

(C29)

(C30)

(C31)

(C32)

(C33)

(C34)

(C35)

(C36)

(C37)

(C38)

(C39)

(U1) (U2) (U3) (U4)(U5)

Figure 6 The hierarchical structure of risk evaluation

0

10

20

30

40

50

60

70

80

90

100

The o

btai

ned

frequ

ency

of e

ach

indi

cato

r

Risk indicator

C1

C3

C5

C7

C9

C11

C13

C15

C17

C19

C21

C23

C25

C27

C29

C31

C33

C35

C37

C39

High riskModerate riskLow risk

Figure 7 The obtained frequency of each indicator with differentrisk levels

Table 2 Nine-point comparison scale

Scale (119886119894119895) Meaning

1 Indicator 119909119894is of the same importance as indicator 119909

119895

3 Indicator 119909119894is slightly more important than indicator

119909119895

5 Indicator 119909119894is obviously more important than

indicator 119909119895

7 Indicator 119909119894is strongly more important than

indicator 119909119895

9 Indicator 119909119894is extremely more important than

indicator 119909119895

2 4 6 8 Middle value of aboveReciprocal 119909

119894119909119895= 119886119894119895 then 119909

119895119909119894= 119886119895119894

= 1119886119894119895

443 Substep 3 Determine the Weight Vector of Risk IndexAfter the judgment matrix is obtained the order weightvector of risk index can be calculated by using Eigenvalue

8 Mathematical Problems in Engineering

Table 3 Pairwise comparison judgment matrixes and weights in criteria layer

1198801

1198802

1198803

1198804

1198805

Weight1198801

100 090 140 180 065 0201198802

111 100 150 165 070 0221198803

071 067 100 125 045 0151198804

056 061 080 100 040 0121198805

154 143 222 250 100 031120582max = 50034 CI = 000084 CR = 000075 lt 01

Table 4 Judgment matrixes and weights of ldquopolicy and law riskrdquo criteria

Policy and law risk 1198621

1198622

1198623

1198624

1198625

1198626

Local weight1198621

100 300 050 250 080 350 0201198622

033 100 020 090 033 120 0071198623

200 500 100 450 200 520 0371198624

040 111 022 100 030 160 0081198625

125 300 050 333 100 320 0221198626

029 083 019 063 031 100 006120582max = 60297 CI = 00059 CR = 00048 lt 01

Table 5 Judgment matrixes and weights of ldquomanagement riskrdquo criteria

Managementrisk 119862

71198628

1198629

11986210

11986211

11986212

11986213

11986214

11986215

11986216

11986217

11986218

11986219

11986220

11986221

11986222 Local weight

1198627

100 033 029 050 067 025 028 050 024 028 091 056 077 083 083 091 003

1198628

300 100 091 120 150 067 071 130 040 067 250 180 200 220 230 250 007

1198629

350 110 100 150 250 083 100 150 083 100 250 200 260 280 280 300 009

11986210

200 083 067 100 120 050 056 100 045 067 150 120 150 160 160 180 006

11986211

150 067 040 083 100 033 045 077 029 040 130 083 110 120 120 130 004

11986212

400 150 120 200 300 100 120 180 083 120 320 200 280 300 300 320 011

11986213

360 140 100 180 220 083 100 160 083 100 280 180 220 230 230 250 009

11986214

200 077 067 100 130 056 063 100 050 056 180 110 150 160 160 180 006

11986215

420 250 120 220 350 120 120 200 100 120 400 220 300 320 320 350 012

11986216

360 150 100 150 250 083 100 180 083 100 250 180 220 240 240 250 009

11986217

110 040 040 067 077 031 036 056 025 040 100 067 083 091 091 100 003

11986218

180 056 050 083 120 050 056 091 045 056 150 100 150 160 160 180 005

11986219

130 050 038 067 091 036 045 067 033 045 120 067 100 120 120 110 004

11986220

120 045 036 063 083 033 043 063 031 042 110 063 083 100 100 110 004

11986221

120 043 036 063 083 033 043 063 031 042 110 063 083 100 100 110 004

11986222

110 04 033 056 077 031 040 056 029 040 100 056 091 091 091 100 003120582max = 16055 CI = 0003697 CR = 00023 lt 01

method The eigenvector of judgment matrix with the max-imum eigenvalue is the weight vector of risk index whichdenotes the relative importance of indicators in the same levelwith regard to the indicators in the upper layer The weightvector of risk index is the relative importance of indicators

with regard to the upper layer indicator which is also calledthe local weight

In this paper the weights of indictors in criteria layer andlocal weights of indicators in index layer are calculated whichare lists in Tables 3ndash8 respectively

Mathematical Problems in Engineering 9

Table 6 Judgment matrixes and weights of ldquotechnology riskrdquo criteria

Technology risk 11986223

11986224

11986225

11986226

11986227

11986228

11986229

11986230

11986231

Local weight11986223

100 067 222 222 125 167 111 100 250 01411986224

150 100 286 333 167 250 143 133 333 02011986225

045 035 100 111 059 080 056 050 125 00711986226

045 030 090 100 056 071 050 045 111 00611986227

080 060 170 180 100 133 083 080 200 01111986228

060 040 125 140 075 100 067 067 143 00911986229

090 070 180 200 120 150 100 091 222 01311986230

100 075 200 220 125 150 110 100 250 01411986231

040 030 080 090 050 070 045 040 100 006120582max = 900585 CI = 0000731 CR = 0000504 lt 01

Table 7 Judgment matrixes and weights of ldquonatural environmentriskrdquo criteria

Natural environment risk 11986232

11986233

Local weight11986232

1 18 06411986233

056 1 036120582max = 2 CI = 0 CR = 0 lt 01

444 Substep 4 Consistency Test The consistency of relativeimportance judgment on each indicator made by expertsand engineers is the key prerequisite for using the AHP todetermine the weights of risk indicators Hence it is verynecessary to test the consistency of judgment matrix Whenthe consistency of judgmentmatrix is satisfied themaximumeigenvalue of the judgmentmatrix120582max should be equal to thenumber of indicators which are related to two consistencytest indices namely CI and CR

Consistency index (CI) which measures the divergenceof judgment matrix away from the consistency is defined asfollows

CI =120582max minus 119899

119899 minus 1 (1)

where 119899 represents the number of indicesThus the consistency ratio (CR) is defined as follows

CR =CIRI

(2)

RI is the random consistency index which is the averagevalue of eigenvalues obtained by calculating the judgmentmatrix for more than 500 times The value of RI is given inTable 9

If CR lt 01 the weight vector is acceptable otherwisethe modification of the pairwise judgment matrix is needed

As listed in the last row in Tables 3ndash8 respectivelyall the pairwise comparison judgment matrixes satisfy theconsistency test

445 Substep 5 Calculate the Index Weight The globalweight of each indicator can be determined by multiplying

the local weight of the indicator with theweight of upper layerindicator which locates in the parent node above it

The local and global weights of each risk indicator inindex layer and the weight of each indicator in criteria layerare calculated which are listed in Table 10

45 Step 5 Calculate the Fuzzy Relation Matrix Accordingto the statistical result of the questionnaire by using a certainmathematical method such as frequency-based method andweighted averagemethod the first-level fuzzy relationmatrixR can be calculated as follows

R = (119903119894119895)119899times119898

=

[[[[

[

11990311

11990312

1199031119898

11990321

11990322

1199032119898

1199031198991

1199031198992

119903119899119898

]]]]

]

(3)

where 119903119894119895is the membership degree of the 119895th remark in

remark set V for the indicator 119894 119894 = 1 2 119899 119895 =

1 2 119898 119899 is the number of indices and 119898 is the numberof risk grades in remark set V Different rows in the fuzzyrelation matrix R reflect the different membership degrees ofevaluated object subject to fuzzy set of each grade consideringdifferent evaluation indices

The frequency-based method is used to establish thefuzzy relation matrix in this paper the principle of which isif the number of experts and engineers who judge the ldquohighriskrdquo ldquomoderate riskrdquo and ldquolow riskrdquo is119898

1 1198982 and119898

3respec-

tively then the set (1198981sum3

119896=1119898119896 1198982sum3

119896=1119898119896 1198983sum3

119896=1119898119896)

is the membership set of the evaluation index The obtainedfrequency of each indicator with different risk grades is listedin Figure 7

Thus the first-level fuzzy relation matrix R can becalculated just as follows

1198771=

[[[[[[[

[

01277 04574 04149

04255 03830 05745

02660 05745 01595

00426 05638 03936

01702 03192 05106

00213 03617 06170

]]]]]]]

]

10 Mathematical Problems in Engineering

1198772=

[[[[[[[[[[[[[[[[[[[[[[[[[[

[

00106 04362 05532

00957 04894 04149

01170 05532 03298

00957 03298 05745

00638 04681 04681

01489 03617 04894

01383 04894 03723

00745 04787 04468

01596 03723 04681

01170 06915 01915

00426 04574 05000

00851 03830 05319

00532 04681 04787

00426 04149 05425

00426 04574 05000

00213 05638 04149

]]]]]]]]]]]]]]]]]]]]]]]]]]

]

1198773=

[[[[[[[[[[[[

[

01170 04787 04043

02021 04149 03830

00638 04575 04787

00532 04255 05213

00851 07447 01702

00638 07766 01596

00851 08404 00745

00958 07340 01702

00532 03191 06277

]]]]]]]]]]]]

]

1198774= [

01702 04468 03830

00106 05213 04681]

1198775=

[[[[[[[

[

02447 05638 01915

00957 05000 04043

02340 04787 02872

01064 04894 04042

00957 04681 04362

00638 05532 03830

]]]]]]]

]

(4)

46 Step 6 Make Fuzzy Composition Synthesize the first-level fuzzy relation matrix R with the local weight 119882

119871 and

then the membership matrix 119861119894could be obtained which is

call the first-level fuzzy comprehensive evaluation matrix

119861119894= 119882119871o119877 = (119887

1198941 1198871198942 119887

119894119898) (5)

Due to the hierarchical structure of the evaluation indexsystem the second-level fuzzy relation matrix 119877

1015840 needs to becalculated

1198771015840=

[[[[

[

1198611

1198612

119861119896

]]]]

]

=[[[

[

11988711

11988712

sdot sdot sdot 1198871119898

11988721

11988722

sdot sdot sdot 1198872119898

sdot sdot sdot sdot sdot sdot sdot sdot sdot sdot sdot sdot

1198871198961

1198871198962

sdot sdot sdot 119887119896119898

]]]

]

(6)

Then combined with the weight matrix 119882 the second-level fuzzy comprehensive evaluation matrix B can be calcu-lated as follows

B = 119882o1198771015840 = (1198871 1198872 119887

119898) (7)

where 119887119898is the membership degree of the 119898th remark in

remark set VIn this paper the first-level fuzzy comprehensive evalua-

tion matrix 119861119894is calculated as follows

1198611= 1198821198711o1198771

= (020 007 037 008 022 006)

o

[[[[[[[

[

01277 04574 04149

04255 03830 05745

02660 05745 01595

00426 05638 03936

01702 03192 05106

00213 03617 06170

]]]]]]]

]

= (01690 04679 03631)

(8)

Similarly we can obtain

1198612= (01005 04585 04310)

1198613= (01073 05905 03022)

1198614= (01128 04736 04136)

1198615= (01710 05133 03157)

(9)

Then we obtain the second-level fuzzy relationmatrix1198771015840

1198771015840=

[[[[[

[

01690 04679 03631

01005 04585 04310

01073 05905 03022

01128 04736 04136

01710 05133 03157

]]]]]

]

(10)

The second-level fuzzy comprehensive evaluation matrixB can be calculated as follows

B = 119882o1198771015840

= (020 022 015 012 031)

o[[[[[

[

01690 04679 03631

01005 04585 04310

01073 05905 03022

01128 04736 04136

01710 05133 03157

]]]]]

]

= (01385 04990 03603)

(11)

47 Step 7 Rate and Conclude the Grade Level Accordingto the maximum membership degree principle when 119887

1198940=

max 119887119894(1 le 119894 le 119898) we can judge that the evaluated object

belongs to the 1198940grade

In this paper since 1198872

= max 119887119894(1 le 119894 le 3) =

04990 it is shown that the risk grade of ldquoZhejiang-FuzhourdquoUHV power transmission construction project belongs toldquomoderaterdquo which means the occurrence probability of thisproject risk is medium and the risk occurrence will causegeneral loss So it is necessary for the project managers to

Mathematical Problems in Engineering 11

Table 8 Judgment matrixes and weights of ldquosociety riskrdquo criteria

Society risk 11986234

11986235

11986236

11986237

11986238

11986239

Local weight11986234

1 23 12 18 2 3 02911986235

043 1 05 08 09 13 01211986236

083 2 1 15 17 25 02411986237

056 125 067 1 11 17 01611986238

05 011 059 091 1 15 01011986239

033 077 04 059 067 1 009120582max = 59109 CI = minus00178 CR = minus00141 lt 01

Table 9 The value of RI

119899 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15RI 0 052 089 112 126 136 141 145 149 152 154 156 157 158

carry out some specific risk control measures to make theconstruction of this project run successfully

At the meantime valuing the evaluation result of indi-cators in criteria layer in centesimal form can help projectmanagers to analyze the project riskmore efficiently Supposethe comment set V = [V

1 V2 V3] = 90 50 10 and then

the centesimal value of each indicator in criteria layer can becalculated as follows

1198801= 01690 times 90 + 04679 times 50 + 03631 times 10

= 422383

1198802= 01005 times 90 + 04585 times 50 + 04310 times 10

= 362830

1198803= 01073 times 90 + 05905 times 50 + 03022 times 10

= 422

1198804= 01128 times 90 + 04736 times 50 + 04136 times 10

= 379660

1198805= 01710 times 90 + 05133 times 50 + 03157 times 10

= 442085

(12)

The centesimal value (119880) of risk evaluation of ldquoZhejiang-Fuzhourdquo UHV power transmission construction project canbe calculated as

119880 = 01385 times 90 + 04990 times 50 + 03603 times 10

= 410205

(13)

Figure 8 compares the centesimal value of each indicatorin criteria layer and we can see

1198805≻ 1198801≻ 1198803≻ 119880 ≻ 119880

4≻ 1198802 (14)

Therefore the centesimal value of ldquosociety riskrdquo is thehighest followed by ldquopolicy and law riskrdquo ldquotechnology riskrdquoldquonatural environmental riskrdquo and ldquomanagement riskrdquo Thecentesimal values of both ldquomanagement riskrdquo and ldquonatural

422383

36283

422

37966

442085

Policy and law

Management

Technology

Natural environmental

Society

Centesimal value

Centesimal value of U

risk

risk

risk

risk

risk0 5 10 15 20 25 30 35 40 45 50

Figure 8 Centesimal value of each indicator in criteria layer

environmental riskrdquo are lower than that of the project119880 whilethe centesimal values of other three indicators are larger thanthat of the project 119880 The criteria ldquoSociety riskrdquo ldquopolicy andlaw riskrdquo and ldquotechnology riskrdquo should be paidmore attentionin the risk management and control for ldquoZhejiang-FuzhourdquoUHV power transmission construction project

5 Risk Control Recommendations

According to the risk evaluation result we should paymore attention to ldquosociety riskrdquo ldquopolicy and law riskrdquo andldquotechnology riskrdquoThe specific risk control recommendationsare as follows

51 Risk Control Recommendations for ldquoSociety Riskrdquo

(1) Before and during the construction of ldquoZhejiang-Fuzhourdquo UHV power transmission project the pro-paganda work should be done in the form of TVradio newspapers brochures and so on The con-struction significance and engineering safety knowl-edge related to this project should be propagandizedin order to eliminate the worries from society fol-lowers and local villagers about this UHV powertransmission project

12 Mathematical Problems in Engineering

Table 10 The weight of risk indicators

Criteria layer Index layerIndicator Weight (119882) Indicator Local weight (119882

119871) Global weight (119882

119866)

Policy and law risk (1198801) 020

1198621

020 004001198622

007 001401198623

037 007401198624

008 001601198625

022 004401198626

006 00120

Management risk (1198802) 022

1198627

003 000661198628

007 001541198629

009 0019811986210

006 0013211986211

004 0008811986212

011 0024211986213

009 0019811986214

006 0013211986215

012 0026411986216

009 0019811986217

003 0006611986218

005 0011011986219

004 0008811986220

004 0008811986221

004 0008811986222

003 00066

Technology risk (1198803) 015

11986223

014 0021011986224

020 0030011986225

007 0010511986226

006 0009011986227

011 0016511986228

009 0013511986229

013 0019511986230

014 0021011986231

006 00090

Natural environment risk (1198804) 012 119862

32064 00768

11986233

036 00432

Society risk (1198805) 031

11986234

029 0089911986235

012 0037211986236

024 0074411986237

016 0049611986238

01 0031011986239

009 00279

(2) Grid company should try to sign a contract withlocal government which strives to make the localgovernment be responsible for land requisition houserelocation and crop compensation Grid companycan also set up aworking group to coordinate with thelocal government The determination of land com-pensation standards not only abides by the relevantlaws and regulations but also takes the opinions oflocal masses into consideration

(3) The terrain and ecological resources along the projectline should be fully understood when selecting theoptimal route Having some experienced practition-ers on the team and considering the local customsare better for the route determination During theproject construction the water and soil loss as wellas deforestation should be reduced as far as possibleWhen the project is finished the vegetation should berestored timely

Mathematical Problems in Engineering 13

(4) Keep close touch with the local government andpublic security organization in order to strengthen thesecurity of project construction the ldquomass incidentsrdquosuch as petitions demagoguism and demonstrationshould be paid close attention and some relatedmeasures such as propaganda and negotiation shouldbe taken timely strengthen the project constructionmanagement and perform civilized construction andreduce the negative impacts on local residents to aminimum

52 Risk Control Recommendations for ldquoPolicy and Law Riskrdquo

(1) The project-related personnel especially the projectmanagers should carefully study the policies andlaws related to land management deforestation loanand environmental protection and the related legalcounsel should be engaged in order to reduce the legalrisk during the project construction

(2) Strengthen the research on the policies and guidancedocuments related to energy development and plan-ning

(3) Strengthen the communication with the governmentdepartment to improve the efficiency of project exam-ination and approval

(4) Because the size and weight of UHV equipment arebigger and heavier the traffic laws and regulationsshould be carefully studied to avoid the conflictrelated to UHV equipment transportation Trans-portation limitations should be taken into considera-tion when selecting the UHV equipment and surveyon the transport route is very necessary

53 Risk Control Recommendations for ldquoTechnology Riskrdquo

(1) Track the meteorological information timely andarrange the construction plan according to theweather condition some necessary measures shouldbe taken to protect the equipment from rainwatersuch as building the temporary drain and increasingthe pumping equipment

(2) The earth-rock excavation should keep a reasonableproportion based on the quantity calculation

(3) For waterway transport due to the constant changeof shipping lane the simulation navigation shouldbe performed six months in advance to ensure thetransportation safety

(4) Measure the earth resistivity and design the ground-ing grid establish special subjects to study the impactsof ground resistance on UHVGIS equipment and theoperation of control and protection system

(5) Design the crossing construction based on differ-ent crossing facilities to reduce the risk and diffi-culty when crossing the electricity lines the crossingscheme should be designed at the design stage and

take the terrain characteristic along the project lineinto consideration

(6) The material transport plan should take weather andtransportation environment into consideration opti-mize the use of different transportation facilities andmake the fullest use of crawler-transporter vehicleand cableway

6 Conclusions

In this paper a hybrid evaluation model based on AHPand FCE method is implemented to evaluate the risk ofldquoZhejiang-Fuzhourdquo UHV power transmission constructionprojectThis hybrid evaluationmodel takes full advantages ofAHP and FCEmethod After the risk evaluation index systemis built the AHP is used to determine the index weightand FCE method is used to evaluate the project risk Finallythe specific risk control recommendations are proposed Themain results of risk evaluation of ldquoZhejiang-Fuzhourdquo UHVpower transmission construction project are as follows

(1) The risk grade of ldquoZhejiang-Fuzhourdquo UHV powertransmission construction project belongs to ldquomod-eraterdquo which indicates the occurrence probability ofproject risk is medium and the risk occurrence willcause general loss

(2) ldquoSociety riskrdquo has the highest level and the next isldquopolicy and law riskrdquo ldquotechnique riskrdquo ldquonatural envi-ronmental riskrdquo and ldquomanagement riskrdquo respectivelyldquosociety riskrdquo ldquopolicy and law riskrdquo and ldquotechnologyriskrdquo should be paid more attention in the risk man-agement and control for ldquoZhejiang-Fuzhourdquo UHVpower transmission construction project

(3) Risk control recommendations for main risk criteriawhich include society risk policy and law risk andtechnology risk are proposed

(4) This hybrid evaluation model is feasible and effectivewhich can effectively evaluate the risk of UHV powertransmission construction project

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

This study is supported by the Humanity and Social Scienceproject of the Ministry of Education of China (Project no11YJA790217) and the National Natural Science Foundationof China (Project no 71373076)

References

[1] J P Liu D X Niu and X H Song ldquoThe energy supply anddemand pattern of China a review of evolution and sustainabledevelopmentrdquo Renewable and Sustainable Energy Reviews vol25 pp 220ndash228 2013

14 Mathematical Problems in Engineering

[2] C C Lin C H Yang and J Z Shyua ldquoA comparison ofinnovation policy in the smart grid industry across the pacificchina and the USArdquo Energy Policy vol 57 pp 119ndash132 2013

[3] M Bolinger and R Wiser ldquoA comparative analysis of businessstructures suitable for farmer-ownedwind power projects in theUnited Statesrdquo Energy Policy vol 34 no 14 pp 1750ndash1761 2006

[4] S Grassi N Chokani and R S Abhari ldquoLarge scale technicaland economical assessment of wind energy potential with a GIStool case study Iowardquo Energy Policy vol 45 pp 73ndash85 2012

[5] MHellstrom I Ruuska KWikstrom andD Jafs ldquoProject gov-ernance and path creation in the early stages of Finnish nuclearpower projectsrdquo International Journal of Project Managementvol 31 no 5 pp 712ndash723 2013

[6] P Baumann and G Stevanella ldquoFish passage principles to beconsidered for medium and large dams the case study of afish passage concept for a hydroelectric power project on theMekong mainstem in Laosrdquo Ecological Engineering vol 48 pp79ndash85 2012

[7] W Amatayakul and G Berndes ldquoDetermining factor for thedevelopment of CDM biomass power projectsrdquo Energy forSustainable Development vol 16 pp 197ndash203 2012

[8] J L Liu Q X Li and Y H Wang ldquoRisk analysis in ultradeep scientific drilling project-A fuzzy synthetic evaluationapproachrdquo International Journal of Project Management vol 31no 3 pp 449ndash458 2013

[9] A Badri S Nadeau and A Gbodossou ldquoA new practicalapproach to risk management for underground mining projectin Quebecrdquo Journal of Loss Prevention in the Process Industriesvol 26 no 6 pp 1145ndash1158 2013

[10] J B Song D R Song X Q Zhang and Y Sun ldquoRiskidentification for PPP waste-to-energy incineration projects inChinardquo Energy Policy vol 61 pp 953ndash962 2013

[11] Y Hu J F Du X Z Zhang et al ldquoAn integrative frameworkfor intelligent software project risk planningrdquo Decision SupportSystems vol 55 no 4 pp 927ndash937 2013

[12] T L Saaty The Analytic Hierarchy Process McGraw-Hill NewYork NY USA 1980

[13] M P Amiri ldquoProject selection for oil-fields development byusing the AHP and fuzzy TOPSIS methodsrdquo Expert Systemswith Applications vol 37 no 9 pp 6218ndash6224 2010

[14] H Z Li and S Guo ldquoExternal economies evaluation of windpower engineering project based on analytic hierarchy processand matter-element extension modelrdquo Mathematical Problemsin Engineering vol 2013 Article ID 848901 11 pages 2013

[15] F-G Chen H-L Yao andW-G Shi ldquoApplication of fuzzy andsynthetic judgment to risk assessment of dammed lakerdquo Journalof Shanghai Jiaotong University vol 45 no 1 pp 67ndash75 2011

[16] K Fang B-F He M Yang and Z-C Wang ldquoApplication offuzzy comprehensive evaluation method to CENSrdquo Journal ofHarbin Institute of Technology vol 43 no 5 pp 30ndash36 2011

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Mathematical Problems in Engineering

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Differential EquationsInternational Journal of

Volume 2014

Applied MathematicsJournal of

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Function Spaces

Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of Mathematics and Mathematical Sciences

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Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Stochastic AnalysisInternational Journal of

2 Mathematical Problems in Engineering

power project issues put their attentions on power generationprojects [3ndash7] and some researchers evaluate the risk ofultra-deep scientific drilling project [8] undergroundminingproject [9] PPP waste-to-energy incineration projects [10]intelligent software project [11] and so on However it is veryregretful to find that the risk of UHV power transmissionconstruction project has rarely been studied The risk eval-uation on UHV power transmission construction project canidentify the risk of project and provide some suggestions forthe risk management and control

ldquoZhejiang-Fuzhourdquo UHV power transmission construc-tion project is a key power grid project invested by theState Grid Corporation of China (SGCC) which plays animportant role in keeping the power network operating insafe and stable condition promoting the efficient utilizationof Chinarsquos energy and advancing the regional economicdevelopment The risk of ldquoZhejiang-Fuzhourdquo UHV powertransmission construction project was evaluated by usinganalytic hierarchy process (AHP) and fuzzy comprehensiveevaluation (FCE) method in this paper (the reason whyweselected AHP and FCE method to perform the riskevaluation will be discussed in Section 4) The evaluationresult can identify the risk level of this project point out thekey risk criteria that need to be paid more attention andprovide the basis for the recommendations of controlling theproject risk

The paper is organized as follows Section 2 provides anoverview of ldquoZhejiang-Fuzhourdquo UHV power transmissionconstruction project which lays the foundation for buildingthe risk evaluation index system Section 3 identifies therisk index of ldquoZhejiang-Fuzhourdquo UHV power transmissionconstruction project by using Delphi method and buildsthe risk evaluation index system The risk evaluation ofldquoZhejiang-Fuzhourdquo UHV power transmission constructionproject based on AHP and FCE method is performed inSection 4 Specific risk control recommendations are pro-posed in Section 5 Section 6 concludes this paper

2 Overview of lsquolsquoZhejiang-Fuzhoursquorsquo UHVPower Transmission Construction Project

21 Project Profile ldquoZhejiang-Fuzhourdquo UHV power trans-mission construction project is invested by the SGCC whichconnects the 1000 kV substation located in the north ofZhejiang province and 1000 kV substation located in Fuzhoucity (the provincial capital of Fujian) just as shown inFigure 1 This project will build three new UHV transformersubstations and two 603 km-length AC transmission linesThe static and dynamic investments of this project amountto 20716 and 21336 billion Yuan respectively The capitalrequired in this project is composed of own fund and bankloan which accounts for 20 and 80 respectively As thelegal representative the SGCC is responsible for this projectrsquosconstruction operation and repayment of loan principal andinterest ldquoZhejiang-Fuzhourdquo UHV power transmission con-struction project is very urgent in terms of project durationwhich plans to be put into operation during the ldquo12th Five-Year Planrdquo period If this project can be constructed and put

transmission line

substation1000 kV

1000 kV

Figure 1 Geographical distribution of ldquoZhejiang-Fuzhourdquo UHVpower transmission construction project

into operation as planned the power transmission bottleneckof East China Power System can be mitigated and the safeand reliable operation of East China Power System can alsobe enhanced Meanwhile this project will make preparationfor the future construction of UHV power grid

This project is an important part of building the strongpower grid of East China Power System and it is alsoan ACDC UHV power receiving platform for Zhejiangand Fujian power grid This project plays a crucial role insupporting the safe and stable operation of power grid withUHVDC accessing the Zhejiang power grid Meanwhile itprovides a main power exchange channel from Zhejiang toFujian More importantly this construction project could fillthe electricity gap of Zhejiang power grid and send out thepower surplus of Fujian power grid during the ldquo12th Five-YearPlanrdquo period

22 Project Characteristics ldquoZhejiang-Fuzhourdquo UHV powertransmission construction project has many special charac-teristics just as follows

221 Tight Time According to the milestone plan the UHVtransformer substation project was commenced at the end of2012 while the transmission line excavation was started inMarch 2013 and planned to be completed in December 2014Due to the delaying of approval from the National EnergyAdministration and the relevant preresearching reports it isimpossible to reach the target of being approved at the end ofthis year which will affect the subsequent project tasks suchas construction drawing design project bidding and contractsigning If the operation schedule remains unchanged theeffective project duration will be significantly shortened

Mathematical Problems in Engineering 3

222 Heavy Task For this project the land acquisitionformality is very complicated with heavy workload and longprocess At some substation sites some farms and graves needto be relocated Meanwhile when the project workers carriedout drilling and performed land acquisition some villagersobstructed them by using the negative effect of electromag-netic radiation as an excuse Moreover the transmission linewould pass through the areas with widely distributedmineralresources and numerous nature reserves which will bring anegative impact on the project construction The local folkcustom is another big concern What is more the majorequipment and materials for substationsrsquo and transmissionlinesrsquo constructions need take long time and huge workloadto manufacture which is quite likely to go beyond theproduction capacity of domestic equipment manufacturingenterprises

223 Difficult Construction The construction of ldquoZhejiang-Fuzhourdquo UHV power transmission construction project willface many difficulties The substation project will encounterlarge earthwork cutting-filling and massive piling construc-tionsThe installed equipment is miscellaneous and both theinstallation and testing standards are strict The equipmenttransportation is difficult and many roads and bridges needto be broadened and reinforced The geological feature andfoundation type along the project line are quite complex andthe required construction technique level is highThe terrainalong the project line is undulate with high altitude so it isdifficult to transport the tower construction materials Theproject line crosses a large number of roads and rivers whichmakes the construction more complicated

224 Complicated Environment There are many tasksof ldquoZhejiang-Fuzhourdquo UHV power transmission projectincluding project approval feasibility study design start andcompleted acceptance and so on All these tasks face differentexternal environments Meanwhile with the market openingand economic development in China the numbers of policiesand laws affecting the project construction are increasingIn China the society is relatively stable and harmoniousbut it is undeniable that there are still some problems andcontradictions in some social areas some of which are veryserious that may adversely affect and even hinder this projectconstruction if not handled properly What is more thisproject locates along the southeast coast where the geologicalconditions are quite complex with a lot of mountains andhills

3 Building the Risk Evaluation Index System

Risk index identification is a basis for building the risk eval-uation index system which is the beginning of UHV powertransmission construction project management The goal ofrisk index identification is to identify themost important riskindex Commonly the risk index could be identified by usingDelphimethodwhich relies on the perceptual knowledge andexperience of a panel of experts

Analyze the project characteristics and collect the relevant literatures and

documents

Select the experts in the field of power grid construction and project managers

Design and distribute the questionnaire

Calculate and classify the questionnaire results

Do all the experts hold the same opinion

No

Yes

Obtain the risk factors and build the risk evaluation index system

Figure 2 The procedure of risk index identification

For ldquoZhejiang-Fuzhourdquo UHV power transmission con-struction project based on the project characteristics as wellas the relevant literatures and documents the risk index ofUHV power transmission construction project is identifiedby using Delphi method The risk index identification proce-dure is shown in Figure 2

The questionnaire regarding the risk of ldquoZhejiang-Fuzhourdquo UHV power transmission construction projectincludesmore than 60 risk indicatorsThe experts and projectmanagers conducted the questionnaire survey based on theirknowledge and experience By calculating the questionnaireresults 39 main risk indicators are selected for the ldquoZhejiang-Fuzhourdquo UHV power transmission construction projectwhich are called the second-level risk index According to

4 Mathematical Problems in Engineering

the characteristics of selected risk indicators and the expertadvices these 39 risk indicators are divided into ldquopolicyand law riskrdquo ldquomanagement riskrdquo ldquotechnology riskrdquo ldquonaturalenvironment riskrdquo and ldquosociety riskrdquo which are called thefirst-level risk criteria Therefore the risk evaluation indexsystem of ldquoZhejiang-Fuzhourdquo UHV power transmission con-struction project is built just as shown in Figure 3 FromFigure 3 we can see that the risk evaluation index systemcontains 5 first-level risk criteria and 39 second-level riskindicators

4 Risk Evaluation on lsquolsquoZhejiang-FuzhoursquorsquoUHV Power Transmission ConstructionProject Based on AHP and FCM

Therisk evaluation on ldquoZhejiang-FuzhourdquoUHVpower trans-mission construction project targets the safe and smoothoperation of project Risk evaluation is the combinationof qualitative evaluation and quantitative evaluation Withregard to the UHV power transmission construction projectit is very hard to describe some risk factors with quantitativemethods precisely moreover some risk factors are valuedby experts with certain ambiguity Therefore the risk ofUHV power transmission construction project needs to beevaluated by using a certain fuzzy evaluationmethod In viewof this characteristic the fuzzy comprehensive evaluation(FCE) method is employed in this paper

Determining the weight of each risk indicator is a difficultbut crucial work when using FCEmethod to evaluate the riskof UHV power transmission construction project Whetherthe index weight value is reasonable or not is directly relatedto the reliability of risk evaluation result With regard tothe risk evaluation of UHV power transmission constructionproject it is a multiobjective issue that needs to considermany uncertain factors such as policy society and envi-ronment and so on meanwhile it also has a hierarchicalstructure Therefore the AHP method which can effectivelydeal with the issue with a hierarchical structure and considerthe wisdom and experience of expert to overcome theuncertain factors is selected to determine the risk indexweight

The AHP is a multiobjective decision-making tool com-bining qualitative and quantitative analysis [12] Its principleis as follows firstly divide the research issue into a hierarchi-cal structure based on the interrelationship and membershipbetween indicators secondly compare the importance ofeach indicator within the same layer with regard to theupper layer depending on the experience or intuition ofexperts thirdly obtain the importance of each indicatorwith regard to the final object through the hierarchicalstructure and use the consistency test to justify the resultaccuracy [13 14] The risk evaluation index system of UHVpower transmission construction project is such a systemthat contains a multilevel hierarchical structure and existscorrelation among indicators Therefore it is suitable to useAHP method to determine the weights of risk indicators

FCE method intended to quantify the vague factorswhich are difficult to quantify based on fuzzy mathematical

Table 1 The meaning of different risk types

Risk types Meaning

High risk The occurrence probability of project risk is greatand the risk occurrence will cause huge loss

Moderate riskThe occurrence probability of project risk ismedium and the risk occurrence will causegeneral loss

Low risk The occurrence probability of project risk is lowand the risk occurrence will cause small loss

method is a fuzzy bottom-up multicriteria decision making(MCDM) method [15 16] As a specific application of fuzzymathematics method FCE method was proposed by theChinese scholar P Z Wang Considering the various factorsassociated with the evaluation system the FCE method usesthe fuzzy linear transformation principle and maximummembership degree principle to quantify the fuzzy indicators

The framework of risk evaluation on ldquoZhejiang-FuzhourdquoUHV power transmission construction project based onAHP and FCMmethod is shown in Figure 4

The specific calculation steps for the risk evaluation onldquoZhejiang-Fuzhourdquo UHV power transmission constructionproject based on AHP and FCE method are as follows

41 Step 1 Building the Risk Evaluation Index System Theriskevaluation index system of ldquoZhejiang-Fuzhourdquo UHV powertransmission construction project has been built in Section 3just as shown in Figure 3

42 Step 2 Determine the Evaluated Object and EvaluationIndex Set For the evaluated object F the evaluation index set119862 = 119862

119894 (119894 = 1 2 119899) is an entiretywith intrinsic structure

composing of the indicators that represent the characteristicsof the evaluated object F

In this paper the evaluated object F is the risk ofldquoZhejiang-Fuzhourdquo UHV power transmission constructionproject The evaluation index set is composed of 39 riskindicators namely 119862 = 119862

119894 (119894 = 1 2 39)

43 Step 3 Give the Remark Set According to the evaluationstandard and grade the remark set V = [V

1 V2 V

119898] can

be made based on the opinions of experts and engineersconsidering the qualitative index and quantitative indextogether The remark set V is composed of different riskgrades and 119898 in the remark set V represents the number ofrisk grades

In this paper according to the characteristics ofldquoZhejiang-Fuzhourdquo UHV power transmission constructionproject and the expertise suggestion in the field of powergrid construction project the evaluated risk is divided intothree types namely ldquohigh riskrdquo ldquomoderate riskrdquo and ldquolowriskrdquo the meanings of which are listed in Table 1 Thus theremark set V can be made namely V = [V

1 V2 V3]

Mathematical Problems in Engineering 5

ldquoZhejiang-Fuzhourdquo

UHV power transmission construction

project

Policy and law risk

Technology risk

Society risk

Natural environmentrisk

Management risk

Project approval policy risk

Loan policy risk

Environmental protection law risk

Unsound traffic law risk

Adjustment risk on energy development strategyand electric planning policyLand requisition and logging policy risk

Quality management risk

Security management riskGoods and material management risk

Contract management risk

Bidding management risk

Project budget risk

Project design risk

Feasibility research risk

Other department coordination risk

Operation preparation riskCompletion inspection and approval risk

Debugging riskImmature contractor risk

Supervision risk

Investment risk

Schedule risk

Substation construction risk

Technical immature risk

Depopulated zone construction risk

Mountain material transportation risk

Tower construction risk

Important line crossing risk

Equipment installation risk

Grounding project resistance reduction risk

Large equipment transportation risk

Social and public opinion risk

Possible social risk due to immature regime

Life security concern risk

Maladjustment risk to the living environment changes

Possible ecological damage risk

Land requisition removing and crop compensation risk

Natural disaster risk

Adverse geological condition risk

Figure 3 The risk evaluation index system of ldquoZhejiang-Fuzhourdquo UHV power transmission construction project

6 Mathematical Problems in Engineering

Construct the hierarchical structure model

Construct the judgment matrixes

Determine the weight vector of risk index

Consistency test

Satisfied

Determine the evaluated object and evaluation index set

Give the remark set

Determine the index weight

Calculate the fuzzy relation matrix

Make fuzzy composition

Rate and conclude the grade level

AHP method to determine index weight

Nonsatisfied

Build the risk evaluation index system

Figure 4 The framework of risk evaluation

44 Step 4Determine the IndexWeight byUsingAHPMethodIn this paper the AHP method is employed to determinethe index weight After building the evaluation index systemthe local weight 119882

119871= 1199081198711

1199081198712

119908119871119899

and global weight119882119866

= 1199081198661

1199081198662

119908119866119899

of indicators in index layer andthe weight119882 = 119908

1 1199082 119908

ℎ of indicators in criteria layer

can be calculated where sum119899

119894=1119908119866119894

= 1 sumℎ119894=1

119908119894= 1 0 le 119908

119866119894

119908119894le 1

441 Substep 1 Construct the Hierarchical Structure ModelAccording to the overall goal and characteristics of MCDMproblem the complex determination of index weight isdecomposed and framed as a bottom-up hierarchical struc-ture which includes the goal layer criteria layer and indexlayer just as shown in Figure 5

In this paper the risk evaluation index system contains5 first-level risk criteria and 39 second-level risk indicatorsSuppose 119880 = 119880

1 1198802 1198803 1198804 1198805 = policy and law risk

management risk technology risk natural environment risksociety risks 119862 = 119862

1 1198622 119862

39 = project approval

policy risk adjustment risk on energy development strategyand electric planning policy land requisition and loggingpolicy risk social and public opinion risk The bottom-up hierarchical structure of risk evaluation of ldquoZhejiang-Fuzhourdquo UHV power transmission construction project isshown in Figure 6

Goal

Index

Criteria middot middot middot middot middot middot

middot middot middot middot middot middot middot middot middot

middot middot middot middot middot middot middot middot middot

Figure 5 The hierarchical structure of AHP for determining theindex weights

442 Substep 2 Construct the Judgment Matrixes The AHPuses the pairwise comparison method to construct thejudgmentmatrixes for both criteria layer and index layerThepairwise comparison is performed by using a nine-point scalewhich can convert human preference into quantitative valuejust as shown in Table 2

According to the analysis shown in Table 2 it shows that119886119894119895

gt 0 119886119894119894= 1 119886

119895119894= 1119886119894119895

In this paper after recognizing the judgments and opin-ions of experts and engineers related to UHV power trans-mission construction project according to the questionnaireresult the judgment matrixes of criteria layer and index layerby using the nine-point scale pair-wise comparison methodare constructed and the results are shown in Tables 3 4 5 67 and 8

Mathematical Problems in Engineering 7

Criteria

Risk evaluation of ldquoZhejiang-Fuzhourdquo UHV power transmission construction project

Policy and law risk Technology risk

Index

Management risk

Quality management risk

Security management risk

Goods and material management risk

Contract management risk

Bidding management risk

Project budget risk

Project design risk

Feasibility research risk

Other department coordination risk

Operation preparation risk

Completion inspection and approval risk

Debugging risk

Immature contractor risk

Supervision risk

Investment risk

Schedule risk

Project approval policy risk

Loan policy risk

Environmental protection law risk

Unsound traffic law risk

Adjustment risk on energy development strategy and electric

planning policy

Land requisition and logging policy risk

Substation construction risk

Technical immature risk

Depopulated zone construction risk

Mountain material transportation risk

Tower construction risk

Important line crossing risk

Equipment installation risk

Grounding projectresistance reduction risk

Large equipmenttransportation risk

Natural environment risk

Natural disaster

risk

Adverse geological condition

risk

Possible social risk due to immature

regime

Life security concern risk

Maladjustment risk to the living

environment changes

Possible ecological damage risk

Land requisition removing and crop compensation risk

Social and public opinion risk

Society risk

Goal

(C1)

(C2)

(C3)

(C4)

(C5)

(C6)

(C7)

(C8)

(C9)

(C10)

(C11)

(C12)

(C13)

(C14)

(C15)

(C16)

(C17)

(C18)

(C19)

(C20)

(C21)

(C22)

(C23)

(C24)

(C25)

(C26)

(C27)

(C28)

(C29)

(C30)

(C31)

(C32)

(C33)

(C34)

(C35)

(C36)

(C37)

(C38)

(C39)

(U1) (U2) (U3) (U4)(U5)

Figure 6 The hierarchical structure of risk evaluation

0

10

20

30

40

50

60

70

80

90

100

The o

btai

ned

frequ

ency

of e

ach

indi

cato

r

Risk indicator

C1

C3

C5

C7

C9

C11

C13

C15

C17

C19

C21

C23

C25

C27

C29

C31

C33

C35

C37

C39

High riskModerate riskLow risk

Figure 7 The obtained frequency of each indicator with differentrisk levels

Table 2 Nine-point comparison scale

Scale (119886119894119895) Meaning

1 Indicator 119909119894is of the same importance as indicator 119909

119895

3 Indicator 119909119894is slightly more important than indicator

119909119895

5 Indicator 119909119894is obviously more important than

indicator 119909119895

7 Indicator 119909119894is strongly more important than

indicator 119909119895

9 Indicator 119909119894is extremely more important than

indicator 119909119895

2 4 6 8 Middle value of aboveReciprocal 119909

119894119909119895= 119886119894119895 then 119909

119895119909119894= 119886119895119894

= 1119886119894119895

443 Substep 3 Determine the Weight Vector of Risk IndexAfter the judgment matrix is obtained the order weightvector of risk index can be calculated by using Eigenvalue

8 Mathematical Problems in Engineering

Table 3 Pairwise comparison judgment matrixes and weights in criteria layer

1198801

1198802

1198803

1198804

1198805

Weight1198801

100 090 140 180 065 0201198802

111 100 150 165 070 0221198803

071 067 100 125 045 0151198804

056 061 080 100 040 0121198805

154 143 222 250 100 031120582max = 50034 CI = 000084 CR = 000075 lt 01

Table 4 Judgment matrixes and weights of ldquopolicy and law riskrdquo criteria

Policy and law risk 1198621

1198622

1198623

1198624

1198625

1198626

Local weight1198621

100 300 050 250 080 350 0201198622

033 100 020 090 033 120 0071198623

200 500 100 450 200 520 0371198624

040 111 022 100 030 160 0081198625

125 300 050 333 100 320 0221198626

029 083 019 063 031 100 006120582max = 60297 CI = 00059 CR = 00048 lt 01

Table 5 Judgment matrixes and weights of ldquomanagement riskrdquo criteria

Managementrisk 119862

71198628

1198629

11986210

11986211

11986212

11986213

11986214

11986215

11986216

11986217

11986218

11986219

11986220

11986221

11986222 Local weight

1198627

100 033 029 050 067 025 028 050 024 028 091 056 077 083 083 091 003

1198628

300 100 091 120 150 067 071 130 040 067 250 180 200 220 230 250 007

1198629

350 110 100 150 250 083 100 150 083 100 250 200 260 280 280 300 009

11986210

200 083 067 100 120 050 056 100 045 067 150 120 150 160 160 180 006

11986211

150 067 040 083 100 033 045 077 029 040 130 083 110 120 120 130 004

11986212

400 150 120 200 300 100 120 180 083 120 320 200 280 300 300 320 011

11986213

360 140 100 180 220 083 100 160 083 100 280 180 220 230 230 250 009

11986214

200 077 067 100 130 056 063 100 050 056 180 110 150 160 160 180 006

11986215

420 250 120 220 350 120 120 200 100 120 400 220 300 320 320 350 012

11986216

360 150 100 150 250 083 100 180 083 100 250 180 220 240 240 250 009

11986217

110 040 040 067 077 031 036 056 025 040 100 067 083 091 091 100 003

11986218

180 056 050 083 120 050 056 091 045 056 150 100 150 160 160 180 005

11986219

130 050 038 067 091 036 045 067 033 045 120 067 100 120 120 110 004

11986220

120 045 036 063 083 033 043 063 031 042 110 063 083 100 100 110 004

11986221

120 043 036 063 083 033 043 063 031 042 110 063 083 100 100 110 004

11986222

110 04 033 056 077 031 040 056 029 040 100 056 091 091 091 100 003120582max = 16055 CI = 0003697 CR = 00023 lt 01

method The eigenvector of judgment matrix with the max-imum eigenvalue is the weight vector of risk index whichdenotes the relative importance of indicators in the same levelwith regard to the indicators in the upper layer The weightvector of risk index is the relative importance of indicators

with regard to the upper layer indicator which is also calledthe local weight

In this paper the weights of indictors in criteria layer andlocal weights of indicators in index layer are calculated whichare lists in Tables 3ndash8 respectively

Mathematical Problems in Engineering 9

Table 6 Judgment matrixes and weights of ldquotechnology riskrdquo criteria

Technology risk 11986223

11986224

11986225

11986226

11986227

11986228

11986229

11986230

11986231

Local weight11986223

100 067 222 222 125 167 111 100 250 01411986224

150 100 286 333 167 250 143 133 333 02011986225

045 035 100 111 059 080 056 050 125 00711986226

045 030 090 100 056 071 050 045 111 00611986227

080 060 170 180 100 133 083 080 200 01111986228

060 040 125 140 075 100 067 067 143 00911986229

090 070 180 200 120 150 100 091 222 01311986230

100 075 200 220 125 150 110 100 250 01411986231

040 030 080 090 050 070 045 040 100 006120582max = 900585 CI = 0000731 CR = 0000504 lt 01

Table 7 Judgment matrixes and weights of ldquonatural environmentriskrdquo criteria

Natural environment risk 11986232

11986233

Local weight11986232

1 18 06411986233

056 1 036120582max = 2 CI = 0 CR = 0 lt 01

444 Substep 4 Consistency Test The consistency of relativeimportance judgment on each indicator made by expertsand engineers is the key prerequisite for using the AHP todetermine the weights of risk indicators Hence it is verynecessary to test the consistency of judgment matrix Whenthe consistency of judgmentmatrix is satisfied themaximumeigenvalue of the judgmentmatrix120582max should be equal to thenumber of indicators which are related to two consistencytest indices namely CI and CR

Consistency index (CI) which measures the divergenceof judgment matrix away from the consistency is defined asfollows

CI =120582max minus 119899

119899 minus 1 (1)

where 119899 represents the number of indicesThus the consistency ratio (CR) is defined as follows

CR =CIRI

(2)

RI is the random consistency index which is the averagevalue of eigenvalues obtained by calculating the judgmentmatrix for more than 500 times The value of RI is given inTable 9

If CR lt 01 the weight vector is acceptable otherwisethe modification of the pairwise judgment matrix is needed

As listed in the last row in Tables 3ndash8 respectivelyall the pairwise comparison judgment matrixes satisfy theconsistency test

445 Substep 5 Calculate the Index Weight The globalweight of each indicator can be determined by multiplying

the local weight of the indicator with theweight of upper layerindicator which locates in the parent node above it

The local and global weights of each risk indicator inindex layer and the weight of each indicator in criteria layerare calculated which are listed in Table 10

45 Step 5 Calculate the Fuzzy Relation Matrix Accordingto the statistical result of the questionnaire by using a certainmathematical method such as frequency-based method andweighted averagemethod the first-level fuzzy relationmatrixR can be calculated as follows

R = (119903119894119895)119899times119898

=

[[[[

[

11990311

11990312

1199031119898

11990321

11990322

1199032119898

1199031198991

1199031198992

119903119899119898

]]]]

]

(3)

where 119903119894119895is the membership degree of the 119895th remark in

remark set V for the indicator 119894 119894 = 1 2 119899 119895 =

1 2 119898 119899 is the number of indices and 119898 is the numberof risk grades in remark set V Different rows in the fuzzyrelation matrix R reflect the different membership degrees ofevaluated object subject to fuzzy set of each grade consideringdifferent evaluation indices

The frequency-based method is used to establish thefuzzy relation matrix in this paper the principle of which isif the number of experts and engineers who judge the ldquohighriskrdquo ldquomoderate riskrdquo and ldquolow riskrdquo is119898

1 1198982 and119898

3respec-

tively then the set (1198981sum3

119896=1119898119896 1198982sum3

119896=1119898119896 1198983sum3

119896=1119898119896)

is the membership set of the evaluation index The obtainedfrequency of each indicator with different risk grades is listedin Figure 7

Thus the first-level fuzzy relation matrix R can becalculated just as follows

1198771=

[[[[[[[

[

01277 04574 04149

04255 03830 05745

02660 05745 01595

00426 05638 03936

01702 03192 05106

00213 03617 06170

]]]]]]]

]

10 Mathematical Problems in Engineering

1198772=

[[[[[[[[[[[[[[[[[[[[[[[[[[

[

00106 04362 05532

00957 04894 04149

01170 05532 03298

00957 03298 05745

00638 04681 04681

01489 03617 04894

01383 04894 03723

00745 04787 04468

01596 03723 04681

01170 06915 01915

00426 04574 05000

00851 03830 05319

00532 04681 04787

00426 04149 05425

00426 04574 05000

00213 05638 04149

]]]]]]]]]]]]]]]]]]]]]]]]]]

]

1198773=

[[[[[[[[[[[[

[

01170 04787 04043

02021 04149 03830

00638 04575 04787

00532 04255 05213

00851 07447 01702

00638 07766 01596

00851 08404 00745

00958 07340 01702

00532 03191 06277

]]]]]]]]]]]]

]

1198774= [

01702 04468 03830

00106 05213 04681]

1198775=

[[[[[[[

[

02447 05638 01915

00957 05000 04043

02340 04787 02872

01064 04894 04042

00957 04681 04362

00638 05532 03830

]]]]]]]

]

(4)

46 Step 6 Make Fuzzy Composition Synthesize the first-level fuzzy relation matrix R with the local weight 119882

119871 and

then the membership matrix 119861119894could be obtained which is

call the first-level fuzzy comprehensive evaluation matrix

119861119894= 119882119871o119877 = (119887

1198941 1198871198942 119887

119894119898) (5)

Due to the hierarchical structure of the evaluation indexsystem the second-level fuzzy relation matrix 119877

1015840 needs to becalculated

1198771015840=

[[[[

[

1198611

1198612

119861119896

]]]]

]

=[[[

[

11988711

11988712

sdot sdot sdot 1198871119898

11988721

11988722

sdot sdot sdot 1198872119898

sdot sdot sdot sdot sdot sdot sdot sdot sdot sdot sdot sdot

1198871198961

1198871198962

sdot sdot sdot 119887119896119898

]]]

]

(6)

Then combined with the weight matrix 119882 the second-level fuzzy comprehensive evaluation matrix B can be calcu-lated as follows

B = 119882o1198771015840 = (1198871 1198872 119887

119898) (7)

where 119887119898is the membership degree of the 119898th remark in

remark set VIn this paper the first-level fuzzy comprehensive evalua-

tion matrix 119861119894is calculated as follows

1198611= 1198821198711o1198771

= (020 007 037 008 022 006)

o

[[[[[[[

[

01277 04574 04149

04255 03830 05745

02660 05745 01595

00426 05638 03936

01702 03192 05106

00213 03617 06170

]]]]]]]

]

= (01690 04679 03631)

(8)

Similarly we can obtain

1198612= (01005 04585 04310)

1198613= (01073 05905 03022)

1198614= (01128 04736 04136)

1198615= (01710 05133 03157)

(9)

Then we obtain the second-level fuzzy relationmatrix1198771015840

1198771015840=

[[[[[

[

01690 04679 03631

01005 04585 04310

01073 05905 03022

01128 04736 04136

01710 05133 03157

]]]]]

]

(10)

The second-level fuzzy comprehensive evaluation matrixB can be calculated as follows

B = 119882o1198771015840

= (020 022 015 012 031)

o[[[[[

[

01690 04679 03631

01005 04585 04310

01073 05905 03022

01128 04736 04136

01710 05133 03157

]]]]]

]

= (01385 04990 03603)

(11)

47 Step 7 Rate and Conclude the Grade Level Accordingto the maximum membership degree principle when 119887

1198940=

max 119887119894(1 le 119894 le 119898) we can judge that the evaluated object

belongs to the 1198940grade

In this paper since 1198872

= max 119887119894(1 le 119894 le 3) =

04990 it is shown that the risk grade of ldquoZhejiang-FuzhourdquoUHV power transmission construction project belongs toldquomoderaterdquo which means the occurrence probability of thisproject risk is medium and the risk occurrence will causegeneral loss So it is necessary for the project managers to

Mathematical Problems in Engineering 11

Table 8 Judgment matrixes and weights of ldquosociety riskrdquo criteria

Society risk 11986234

11986235

11986236

11986237

11986238

11986239

Local weight11986234

1 23 12 18 2 3 02911986235

043 1 05 08 09 13 01211986236

083 2 1 15 17 25 02411986237

056 125 067 1 11 17 01611986238

05 011 059 091 1 15 01011986239

033 077 04 059 067 1 009120582max = 59109 CI = minus00178 CR = minus00141 lt 01

Table 9 The value of RI

119899 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15RI 0 052 089 112 126 136 141 145 149 152 154 156 157 158

carry out some specific risk control measures to make theconstruction of this project run successfully

At the meantime valuing the evaluation result of indi-cators in criteria layer in centesimal form can help projectmanagers to analyze the project riskmore efficiently Supposethe comment set V = [V

1 V2 V3] = 90 50 10 and then

the centesimal value of each indicator in criteria layer can becalculated as follows

1198801= 01690 times 90 + 04679 times 50 + 03631 times 10

= 422383

1198802= 01005 times 90 + 04585 times 50 + 04310 times 10

= 362830

1198803= 01073 times 90 + 05905 times 50 + 03022 times 10

= 422

1198804= 01128 times 90 + 04736 times 50 + 04136 times 10

= 379660

1198805= 01710 times 90 + 05133 times 50 + 03157 times 10

= 442085

(12)

The centesimal value (119880) of risk evaluation of ldquoZhejiang-Fuzhourdquo UHV power transmission construction project canbe calculated as

119880 = 01385 times 90 + 04990 times 50 + 03603 times 10

= 410205

(13)

Figure 8 compares the centesimal value of each indicatorin criteria layer and we can see

1198805≻ 1198801≻ 1198803≻ 119880 ≻ 119880

4≻ 1198802 (14)

Therefore the centesimal value of ldquosociety riskrdquo is thehighest followed by ldquopolicy and law riskrdquo ldquotechnology riskrdquoldquonatural environmental riskrdquo and ldquomanagement riskrdquo Thecentesimal values of both ldquomanagement riskrdquo and ldquonatural

422383

36283

422

37966

442085

Policy and law

Management

Technology

Natural environmental

Society

Centesimal value

Centesimal value of U

risk

risk

risk

risk

risk0 5 10 15 20 25 30 35 40 45 50

Figure 8 Centesimal value of each indicator in criteria layer

environmental riskrdquo are lower than that of the project119880 whilethe centesimal values of other three indicators are larger thanthat of the project 119880 The criteria ldquoSociety riskrdquo ldquopolicy andlaw riskrdquo and ldquotechnology riskrdquo should be paidmore attentionin the risk management and control for ldquoZhejiang-FuzhourdquoUHV power transmission construction project

5 Risk Control Recommendations

According to the risk evaluation result we should paymore attention to ldquosociety riskrdquo ldquopolicy and law riskrdquo andldquotechnology riskrdquoThe specific risk control recommendationsare as follows

51 Risk Control Recommendations for ldquoSociety Riskrdquo

(1) Before and during the construction of ldquoZhejiang-Fuzhourdquo UHV power transmission project the pro-paganda work should be done in the form of TVradio newspapers brochures and so on The con-struction significance and engineering safety knowl-edge related to this project should be propagandizedin order to eliminate the worries from society fol-lowers and local villagers about this UHV powertransmission project

12 Mathematical Problems in Engineering

Table 10 The weight of risk indicators

Criteria layer Index layerIndicator Weight (119882) Indicator Local weight (119882

119871) Global weight (119882

119866)

Policy and law risk (1198801) 020

1198621

020 004001198622

007 001401198623

037 007401198624

008 001601198625

022 004401198626

006 00120

Management risk (1198802) 022

1198627

003 000661198628

007 001541198629

009 0019811986210

006 0013211986211

004 0008811986212

011 0024211986213

009 0019811986214

006 0013211986215

012 0026411986216

009 0019811986217

003 0006611986218

005 0011011986219

004 0008811986220

004 0008811986221

004 0008811986222

003 00066

Technology risk (1198803) 015

11986223

014 0021011986224

020 0030011986225

007 0010511986226

006 0009011986227

011 0016511986228

009 0013511986229

013 0019511986230

014 0021011986231

006 00090

Natural environment risk (1198804) 012 119862

32064 00768

11986233

036 00432

Society risk (1198805) 031

11986234

029 0089911986235

012 0037211986236

024 0074411986237

016 0049611986238

01 0031011986239

009 00279

(2) Grid company should try to sign a contract withlocal government which strives to make the localgovernment be responsible for land requisition houserelocation and crop compensation Grid companycan also set up aworking group to coordinate with thelocal government The determination of land com-pensation standards not only abides by the relevantlaws and regulations but also takes the opinions oflocal masses into consideration

(3) The terrain and ecological resources along the projectline should be fully understood when selecting theoptimal route Having some experienced practition-ers on the team and considering the local customsare better for the route determination During theproject construction the water and soil loss as wellas deforestation should be reduced as far as possibleWhen the project is finished the vegetation should berestored timely

Mathematical Problems in Engineering 13

(4) Keep close touch with the local government andpublic security organization in order to strengthen thesecurity of project construction the ldquomass incidentsrdquosuch as petitions demagoguism and demonstrationshould be paid close attention and some relatedmeasures such as propaganda and negotiation shouldbe taken timely strengthen the project constructionmanagement and perform civilized construction andreduce the negative impacts on local residents to aminimum

52 Risk Control Recommendations for ldquoPolicy and Law Riskrdquo

(1) The project-related personnel especially the projectmanagers should carefully study the policies andlaws related to land management deforestation loanand environmental protection and the related legalcounsel should be engaged in order to reduce the legalrisk during the project construction

(2) Strengthen the research on the policies and guidancedocuments related to energy development and plan-ning

(3) Strengthen the communication with the governmentdepartment to improve the efficiency of project exam-ination and approval

(4) Because the size and weight of UHV equipment arebigger and heavier the traffic laws and regulationsshould be carefully studied to avoid the conflictrelated to UHV equipment transportation Trans-portation limitations should be taken into considera-tion when selecting the UHV equipment and surveyon the transport route is very necessary

53 Risk Control Recommendations for ldquoTechnology Riskrdquo

(1) Track the meteorological information timely andarrange the construction plan according to theweather condition some necessary measures shouldbe taken to protect the equipment from rainwatersuch as building the temporary drain and increasingthe pumping equipment

(2) The earth-rock excavation should keep a reasonableproportion based on the quantity calculation

(3) For waterway transport due to the constant changeof shipping lane the simulation navigation shouldbe performed six months in advance to ensure thetransportation safety

(4) Measure the earth resistivity and design the ground-ing grid establish special subjects to study the impactsof ground resistance on UHVGIS equipment and theoperation of control and protection system

(5) Design the crossing construction based on differ-ent crossing facilities to reduce the risk and diffi-culty when crossing the electricity lines the crossingscheme should be designed at the design stage and

take the terrain characteristic along the project lineinto consideration

(6) The material transport plan should take weather andtransportation environment into consideration opti-mize the use of different transportation facilities andmake the fullest use of crawler-transporter vehicleand cableway

6 Conclusions

In this paper a hybrid evaluation model based on AHPand FCE method is implemented to evaluate the risk ofldquoZhejiang-Fuzhourdquo UHV power transmission constructionprojectThis hybrid evaluationmodel takes full advantages ofAHP and FCEmethod After the risk evaluation index systemis built the AHP is used to determine the index weightand FCE method is used to evaluate the project risk Finallythe specific risk control recommendations are proposed Themain results of risk evaluation of ldquoZhejiang-Fuzhourdquo UHVpower transmission construction project are as follows

(1) The risk grade of ldquoZhejiang-Fuzhourdquo UHV powertransmission construction project belongs to ldquomod-eraterdquo which indicates the occurrence probability ofproject risk is medium and the risk occurrence willcause general loss

(2) ldquoSociety riskrdquo has the highest level and the next isldquopolicy and law riskrdquo ldquotechnique riskrdquo ldquonatural envi-ronmental riskrdquo and ldquomanagement riskrdquo respectivelyldquosociety riskrdquo ldquopolicy and law riskrdquo and ldquotechnologyriskrdquo should be paid more attention in the risk man-agement and control for ldquoZhejiang-Fuzhourdquo UHVpower transmission construction project

(3) Risk control recommendations for main risk criteriawhich include society risk policy and law risk andtechnology risk are proposed

(4) This hybrid evaluation model is feasible and effectivewhich can effectively evaluate the risk of UHV powertransmission construction project

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

This study is supported by the Humanity and Social Scienceproject of the Ministry of Education of China (Project no11YJA790217) and the National Natural Science Foundationof China (Project no 71373076)

References

[1] J P Liu D X Niu and X H Song ldquoThe energy supply anddemand pattern of China a review of evolution and sustainabledevelopmentrdquo Renewable and Sustainable Energy Reviews vol25 pp 220ndash228 2013

14 Mathematical Problems in Engineering

[2] C C Lin C H Yang and J Z Shyua ldquoA comparison ofinnovation policy in the smart grid industry across the pacificchina and the USArdquo Energy Policy vol 57 pp 119ndash132 2013

[3] M Bolinger and R Wiser ldquoA comparative analysis of businessstructures suitable for farmer-ownedwind power projects in theUnited Statesrdquo Energy Policy vol 34 no 14 pp 1750ndash1761 2006

[4] S Grassi N Chokani and R S Abhari ldquoLarge scale technicaland economical assessment of wind energy potential with a GIStool case study Iowardquo Energy Policy vol 45 pp 73ndash85 2012

[5] MHellstrom I Ruuska KWikstrom andD Jafs ldquoProject gov-ernance and path creation in the early stages of Finnish nuclearpower projectsrdquo International Journal of Project Managementvol 31 no 5 pp 712ndash723 2013

[6] P Baumann and G Stevanella ldquoFish passage principles to beconsidered for medium and large dams the case study of afish passage concept for a hydroelectric power project on theMekong mainstem in Laosrdquo Ecological Engineering vol 48 pp79ndash85 2012

[7] W Amatayakul and G Berndes ldquoDetermining factor for thedevelopment of CDM biomass power projectsrdquo Energy forSustainable Development vol 16 pp 197ndash203 2012

[8] J L Liu Q X Li and Y H Wang ldquoRisk analysis in ultradeep scientific drilling project-A fuzzy synthetic evaluationapproachrdquo International Journal of Project Management vol 31no 3 pp 449ndash458 2013

[9] A Badri S Nadeau and A Gbodossou ldquoA new practicalapproach to risk management for underground mining projectin Quebecrdquo Journal of Loss Prevention in the Process Industriesvol 26 no 6 pp 1145ndash1158 2013

[10] J B Song D R Song X Q Zhang and Y Sun ldquoRiskidentification for PPP waste-to-energy incineration projects inChinardquo Energy Policy vol 61 pp 953ndash962 2013

[11] Y Hu J F Du X Z Zhang et al ldquoAn integrative frameworkfor intelligent software project risk planningrdquo Decision SupportSystems vol 55 no 4 pp 927ndash937 2013

[12] T L Saaty The Analytic Hierarchy Process McGraw-Hill NewYork NY USA 1980

[13] M P Amiri ldquoProject selection for oil-fields development byusing the AHP and fuzzy TOPSIS methodsrdquo Expert Systemswith Applications vol 37 no 9 pp 6218ndash6224 2010

[14] H Z Li and S Guo ldquoExternal economies evaluation of windpower engineering project based on analytic hierarchy processand matter-element extension modelrdquo Mathematical Problemsin Engineering vol 2013 Article ID 848901 11 pages 2013

[15] F-G Chen H-L Yao andW-G Shi ldquoApplication of fuzzy andsynthetic judgment to risk assessment of dammed lakerdquo Journalof Shanghai Jiaotong University vol 45 no 1 pp 67ndash75 2011

[16] K Fang B-F He M Yang and Z-C Wang ldquoApplication offuzzy comprehensive evaluation method to CENSrdquo Journal ofHarbin Institute of Technology vol 43 no 5 pp 30ndash36 2011

Submit your manuscripts athttpwwwhindawicom

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mathematical Problems in Engineering

Hindawi Publishing Corporationhttpwwwhindawicom

Differential EquationsInternational Journal of

Volume 2014

Applied MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mathematical PhysicsAdvances in

Complex AnalysisJournal of

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OptimizationJournal of

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CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Function Spaces

Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of Mathematics and Mathematical Sciences

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The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

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Discrete Dynamics in Nature and Society

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Decision SciencesAdvances in

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Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Stochastic AnalysisInternational Journal of

Mathematical Problems in Engineering 3

222 Heavy Task For this project the land acquisitionformality is very complicated with heavy workload and longprocess At some substation sites some farms and graves needto be relocated Meanwhile when the project workers carriedout drilling and performed land acquisition some villagersobstructed them by using the negative effect of electromag-netic radiation as an excuse Moreover the transmission linewould pass through the areas with widely distributedmineralresources and numerous nature reserves which will bring anegative impact on the project construction The local folkcustom is another big concern What is more the majorequipment and materials for substationsrsquo and transmissionlinesrsquo constructions need take long time and huge workloadto manufacture which is quite likely to go beyond theproduction capacity of domestic equipment manufacturingenterprises

223 Difficult Construction The construction of ldquoZhejiang-Fuzhourdquo UHV power transmission construction project willface many difficulties The substation project will encounterlarge earthwork cutting-filling and massive piling construc-tionsThe installed equipment is miscellaneous and both theinstallation and testing standards are strict The equipmenttransportation is difficult and many roads and bridges needto be broadened and reinforced The geological feature andfoundation type along the project line are quite complex andthe required construction technique level is highThe terrainalong the project line is undulate with high altitude so it isdifficult to transport the tower construction materials Theproject line crosses a large number of roads and rivers whichmakes the construction more complicated

224 Complicated Environment There are many tasksof ldquoZhejiang-Fuzhourdquo UHV power transmission projectincluding project approval feasibility study design start andcompleted acceptance and so on All these tasks face differentexternal environments Meanwhile with the market openingand economic development in China the numbers of policiesand laws affecting the project construction are increasingIn China the society is relatively stable and harmoniousbut it is undeniable that there are still some problems andcontradictions in some social areas some of which are veryserious that may adversely affect and even hinder this projectconstruction if not handled properly What is more thisproject locates along the southeast coast where the geologicalconditions are quite complex with a lot of mountains andhills

3 Building the Risk Evaluation Index System

Risk index identification is a basis for building the risk eval-uation index system which is the beginning of UHV powertransmission construction project management The goal ofrisk index identification is to identify themost important riskindex Commonly the risk index could be identified by usingDelphimethodwhich relies on the perceptual knowledge andexperience of a panel of experts

Analyze the project characteristics and collect the relevant literatures and

documents

Select the experts in the field of power grid construction and project managers

Design and distribute the questionnaire

Calculate and classify the questionnaire results

Do all the experts hold the same opinion

No

Yes

Obtain the risk factors and build the risk evaluation index system

Figure 2 The procedure of risk index identification

For ldquoZhejiang-Fuzhourdquo UHV power transmission con-struction project based on the project characteristics as wellas the relevant literatures and documents the risk index ofUHV power transmission construction project is identifiedby using Delphi method The risk index identification proce-dure is shown in Figure 2

The questionnaire regarding the risk of ldquoZhejiang-Fuzhourdquo UHV power transmission construction projectincludesmore than 60 risk indicatorsThe experts and projectmanagers conducted the questionnaire survey based on theirknowledge and experience By calculating the questionnaireresults 39 main risk indicators are selected for the ldquoZhejiang-Fuzhourdquo UHV power transmission construction projectwhich are called the second-level risk index According to

4 Mathematical Problems in Engineering

the characteristics of selected risk indicators and the expertadvices these 39 risk indicators are divided into ldquopolicyand law riskrdquo ldquomanagement riskrdquo ldquotechnology riskrdquo ldquonaturalenvironment riskrdquo and ldquosociety riskrdquo which are called thefirst-level risk criteria Therefore the risk evaluation indexsystem of ldquoZhejiang-Fuzhourdquo UHV power transmission con-struction project is built just as shown in Figure 3 FromFigure 3 we can see that the risk evaluation index systemcontains 5 first-level risk criteria and 39 second-level riskindicators

4 Risk Evaluation on lsquolsquoZhejiang-FuzhoursquorsquoUHV Power Transmission ConstructionProject Based on AHP and FCM

Therisk evaluation on ldquoZhejiang-FuzhourdquoUHVpower trans-mission construction project targets the safe and smoothoperation of project Risk evaluation is the combinationof qualitative evaluation and quantitative evaluation Withregard to the UHV power transmission construction projectit is very hard to describe some risk factors with quantitativemethods precisely moreover some risk factors are valuedby experts with certain ambiguity Therefore the risk ofUHV power transmission construction project needs to beevaluated by using a certain fuzzy evaluationmethod In viewof this characteristic the fuzzy comprehensive evaluation(FCE) method is employed in this paper

Determining the weight of each risk indicator is a difficultbut crucial work when using FCEmethod to evaluate the riskof UHV power transmission construction project Whetherthe index weight value is reasonable or not is directly relatedto the reliability of risk evaluation result With regard tothe risk evaluation of UHV power transmission constructionproject it is a multiobjective issue that needs to considermany uncertain factors such as policy society and envi-ronment and so on meanwhile it also has a hierarchicalstructure Therefore the AHP method which can effectivelydeal with the issue with a hierarchical structure and considerthe wisdom and experience of expert to overcome theuncertain factors is selected to determine the risk indexweight

The AHP is a multiobjective decision-making tool com-bining qualitative and quantitative analysis [12] Its principleis as follows firstly divide the research issue into a hierarchi-cal structure based on the interrelationship and membershipbetween indicators secondly compare the importance ofeach indicator within the same layer with regard to theupper layer depending on the experience or intuition ofexperts thirdly obtain the importance of each indicatorwith regard to the final object through the hierarchicalstructure and use the consistency test to justify the resultaccuracy [13 14] The risk evaluation index system of UHVpower transmission construction project is such a systemthat contains a multilevel hierarchical structure and existscorrelation among indicators Therefore it is suitable to useAHP method to determine the weights of risk indicators

FCE method intended to quantify the vague factorswhich are difficult to quantify based on fuzzy mathematical

Table 1 The meaning of different risk types

Risk types Meaning

High risk The occurrence probability of project risk is greatand the risk occurrence will cause huge loss

Moderate riskThe occurrence probability of project risk ismedium and the risk occurrence will causegeneral loss

Low risk The occurrence probability of project risk is lowand the risk occurrence will cause small loss

method is a fuzzy bottom-up multicriteria decision making(MCDM) method [15 16] As a specific application of fuzzymathematics method FCE method was proposed by theChinese scholar P Z Wang Considering the various factorsassociated with the evaluation system the FCE method usesthe fuzzy linear transformation principle and maximummembership degree principle to quantify the fuzzy indicators

The framework of risk evaluation on ldquoZhejiang-FuzhourdquoUHV power transmission construction project based onAHP and FCMmethod is shown in Figure 4

The specific calculation steps for the risk evaluation onldquoZhejiang-Fuzhourdquo UHV power transmission constructionproject based on AHP and FCE method are as follows

41 Step 1 Building the Risk Evaluation Index System Theriskevaluation index system of ldquoZhejiang-Fuzhourdquo UHV powertransmission construction project has been built in Section 3just as shown in Figure 3

42 Step 2 Determine the Evaluated Object and EvaluationIndex Set For the evaluated object F the evaluation index set119862 = 119862

119894 (119894 = 1 2 119899) is an entiretywith intrinsic structure

composing of the indicators that represent the characteristicsof the evaluated object F

In this paper the evaluated object F is the risk ofldquoZhejiang-Fuzhourdquo UHV power transmission constructionproject The evaluation index set is composed of 39 riskindicators namely 119862 = 119862

119894 (119894 = 1 2 39)

43 Step 3 Give the Remark Set According to the evaluationstandard and grade the remark set V = [V

1 V2 V

119898] can

be made based on the opinions of experts and engineersconsidering the qualitative index and quantitative indextogether The remark set V is composed of different riskgrades and 119898 in the remark set V represents the number ofrisk grades

In this paper according to the characteristics ofldquoZhejiang-Fuzhourdquo UHV power transmission constructionproject and the expertise suggestion in the field of powergrid construction project the evaluated risk is divided intothree types namely ldquohigh riskrdquo ldquomoderate riskrdquo and ldquolowriskrdquo the meanings of which are listed in Table 1 Thus theremark set V can be made namely V = [V

1 V2 V3]

Mathematical Problems in Engineering 5

ldquoZhejiang-Fuzhourdquo

UHV power transmission construction

project

Policy and law risk

Technology risk

Society risk

Natural environmentrisk

Management risk

Project approval policy risk

Loan policy risk

Environmental protection law risk

Unsound traffic law risk

Adjustment risk on energy development strategyand electric planning policyLand requisition and logging policy risk

Quality management risk

Security management riskGoods and material management risk

Contract management risk

Bidding management risk

Project budget risk

Project design risk

Feasibility research risk

Other department coordination risk

Operation preparation riskCompletion inspection and approval risk

Debugging riskImmature contractor risk

Supervision risk

Investment risk

Schedule risk

Substation construction risk

Technical immature risk

Depopulated zone construction risk

Mountain material transportation risk

Tower construction risk

Important line crossing risk

Equipment installation risk

Grounding project resistance reduction risk

Large equipment transportation risk

Social and public opinion risk

Possible social risk due to immature regime

Life security concern risk

Maladjustment risk to the living environment changes

Possible ecological damage risk

Land requisition removing and crop compensation risk

Natural disaster risk

Adverse geological condition risk

Figure 3 The risk evaluation index system of ldquoZhejiang-Fuzhourdquo UHV power transmission construction project

6 Mathematical Problems in Engineering

Construct the hierarchical structure model

Construct the judgment matrixes

Determine the weight vector of risk index

Consistency test

Satisfied

Determine the evaluated object and evaluation index set

Give the remark set

Determine the index weight

Calculate the fuzzy relation matrix

Make fuzzy composition

Rate and conclude the grade level

AHP method to determine index weight

Nonsatisfied

Build the risk evaluation index system

Figure 4 The framework of risk evaluation

44 Step 4Determine the IndexWeight byUsingAHPMethodIn this paper the AHP method is employed to determinethe index weight After building the evaluation index systemthe local weight 119882

119871= 1199081198711

1199081198712

119908119871119899

and global weight119882119866

= 1199081198661

1199081198662

119908119866119899

of indicators in index layer andthe weight119882 = 119908

1 1199082 119908

ℎ of indicators in criteria layer

can be calculated where sum119899

119894=1119908119866119894

= 1 sumℎ119894=1

119908119894= 1 0 le 119908

119866119894

119908119894le 1

441 Substep 1 Construct the Hierarchical Structure ModelAccording to the overall goal and characteristics of MCDMproblem the complex determination of index weight isdecomposed and framed as a bottom-up hierarchical struc-ture which includes the goal layer criteria layer and indexlayer just as shown in Figure 5

In this paper the risk evaluation index system contains5 first-level risk criteria and 39 second-level risk indicatorsSuppose 119880 = 119880

1 1198802 1198803 1198804 1198805 = policy and law risk

management risk technology risk natural environment risksociety risks 119862 = 119862

1 1198622 119862

39 = project approval

policy risk adjustment risk on energy development strategyand electric planning policy land requisition and loggingpolicy risk social and public opinion risk The bottom-up hierarchical structure of risk evaluation of ldquoZhejiang-Fuzhourdquo UHV power transmission construction project isshown in Figure 6

Goal

Index

Criteria middot middot middot middot middot middot

middot middot middot middot middot middot middot middot middot

middot middot middot middot middot middot middot middot middot

Figure 5 The hierarchical structure of AHP for determining theindex weights

442 Substep 2 Construct the Judgment Matrixes The AHPuses the pairwise comparison method to construct thejudgmentmatrixes for both criteria layer and index layerThepairwise comparison is performed by using a nine-point scalewhich can convert human preference into quantitative valuejust as shown in Table 2

According to the analysis shown in Table 2 it shows that119886119894119895

gt 0 119886119894119894= 1 119886

119895119894= 1119886119894119895

In this paper after recognizing the judgments and opin-ions of experts and engineers related to UHV power trans-mission construction project according to the questionnaireresult the judgment matrixes of criteria layer and index layerby using the nine-point scale pair-wise comparison methodare constructed and the results are shown in Tables 3 4 5 67 and 8

Mathematical Problems in Engineering 7

Criteria

Risk evaluation of ldquoZhejiang-Fuzhourdquo UHV power transmission construction project

Policy and law risk Technology risk

Index

Management risk

Quality management risk

Security management risk

Goods and material management risk

Contract management risk

Bidding management risk

Project budget risk

Project design risk

Feasibility research risk

Other department coordination risk

Operation preparation risk

Completion inspection and approval risk

Debugging risk

Immature contractor risk

Supervision risk

Investment risk

Schedule risk

Project approval policy risk

Loan policy risk

Environmental protection law risk

Unsound traffic law risk

Adjustment risk on energy development strategy and electric

planning policy

Land requisition and logging policy risk

Substation construction risk

Technical immature risk

Depopulated zone construction risk

Mountain material transportation risk

Tower construction risk

Important line crossing risk

Equipment installation risk

Grounding projectresistance reduction risk

Large equipmenttransportation risk

Natural environment risk

Natural disaster

risk

Adverse geological condition

risk

Possible social risk due to immature

regime

Life security concern risk

Maladjustment risk to the living

environment changes

Possible ecological damage risk

Land requisition removing and crop compensation risk

Social and public opinion risk

Society risk

Goal

(C1)

(C2)

(C3)

(C4)

(C5)

(C6)

(C7)

(C8)

(C9)

(C10)

(C11)

(C12)

(C13)

(C14)

(C15)

(C16)

(C17)

(C18)

(C19)

(C20)

(C21)

(C22)

(C23)

(C24)

(C25)

(C26)

(C27)

(C28)

(C29)

(C30)

(C31)

(C32)

(C33)

(C34)

(C35)

(C36)

(C37)

(C38)

(C39)

(U1) (U2) (U3) (U4)(U5)

Figure 6 The hierarchical structure of risk evaluation

0

10

20

30

40

50

60

70

80

90

100

The o

btai

ned

frequ

ency

of e

ach

indi

cato

r

Risk indicator

C1

C3

C5

C7

C9

C11

C13

C15

C17

C19

C21

C23

C25

C27

C29

C31

C33

C35

C37

C39

High riskModerate riskLow risk

Figure 7 The obtained frequency of each indicator with differentrisk levels

Table 2 Nine-point comparison scale

Scale (119886119894119895) Meaning

1 Indicator 119909119894is of the same importance as indicator 119909

119895

3 Indicator 119909119894is slightly more important than indicator

119909119895

5 Indicator 119909119894is obviously more important than

indicator 119909119895

7 Indicator 119909119894is strongly more important than

indicator 119909119895

9 Indicator 119909119894is extremely more important than

indicator 119909119895

2 4 6 8 Middle value of aboveReciprocal 119909

119894119909119895= 119886119894119895 then 119909

119895119909119894= 119886119895119894

= 1119886119894119895

443 Substep 3 Determine the Weight Vector of Risk IndexAfter the judgment matrix is obtained the order weightvector of risk index can be calculated by using Eigenvalue

8 Mathematical Problems in Engineering

Table 3 Pairwise comparison judgment matrixes and weights in criteria layer

1198801

1198802

1198803

1198804

1198805

Weight1198801

100 090 140 180 065 0201198802

111 100 150 165 070 0221198803

071 067 100 125 045 0151198804

056 061 080 100 040 0121198805

154 143 222 250 100 031120582max = 50034 CI = 000084 CR = 000075 lt 01

Table 4 Judgment matrixes and weights of ldquopolicy and law riskrdquo criteria

Policy and law risk 1198621

1198622

1198623

1198624

1198625

1198626

Local weight1198621

100 300 050 250 080 350 0201198622

033 100 020 090 033 120 0071198623

200 500 100 450 200 520 0371198624

040 111 022 100 030 160 0081198625

125 300 050 333 100 320 0221198626

029 083 019 063 031 100 006120582max = 60297 CI = 00059 CR = 00048 lt 01

Table 5 Judgment matrixes and weights of ldquomanagement riskrdquo criteria

Managementrisk 119862

71198628

1198629

11986210

11986211

11986212

11986213

11986214

11986215

11986216

11986217

11986218

11986219

11986220

11986221

11986222 Local weight

1198627

100 033 029 050 067 025 028 050 024 028 091 056 077 083 083 091 003

1198628

300 100 091 120 150 067 071 130 040 067 250 180 200 220 230 250 007

1198629

350 110 100 150 250 083 100 150 083 100 250 200 260 280 280 300 009

11986210

200 083 067 100 120 050 056 100 045 067 150 120 150 160 160 180 006

11986211

150 067 040 083 100 033 045 077 029 040 130 083 110 120 120 130 004

11986212

400 150 120 200 300 100 120 180 083 120 320 200 280 300 300 320 011

11986213

360 140 100 180 220 083 100 160 083 100 280 180 220 230 230 250 009

11986214

200 077 067 100 130 056 063 100 050 056 180 110 150 160 160 180 006

11986215

420 250 120 220 350 120 120 200 100 120 400 220 300 320 320 350 012

11986216

360 150 100 150 250 083 100 180 083 100 250 180 220 240 240 250 009

11986217

110 040 040 067 077 031 036 056 025 040 100 067 083 091 091 100 003

11986218

180 056 050 083 120 050 056 091 045 056 150 100 150 160 160 180 005

11986219

130 050 038 067 091 036 045 067 033 045 120 067 100 120 120 110 004

11986220

120 045 036 063 083 033 043 063 031 042 110 063 083 100 100 110 004

11986221

120 043 036 063 083 033 043 063 031 042 110 063 083 100 100 110 004

11986222

110 04 033 056 077 031 040 056 029 040 100 056 091 091 091 100 003120582max = 16055 CI = 0003697 CR = 00023 lt 01

method The eigenvector of judgment matrix with the max-imum eigenvalue is the weight vector of risk index whichdenotes the relative importance of indicators in the same levelwith regard to the indicators in the upper layer The weightvector of risk index is the relative importance of indicators

with regard to the upper layer indicator which is also calledthe local weight

In this paper the weights of indictors in criteria layer andlocal weights of indicators in index layer are calculated whichare lists in Tables 3ndash8 respectively

Mathematical Problems in Engineering 9

Table 6 Judgment matrixes and weights of ldquotechnology riskrdquo criteria

Technology risk 11986223

11986224

11986225

11986226

11986227

11986228

11986229

11986230

11986231

Local weight11986223

100 067 222 222 125 167 111 100 250 01411986224

150 100 286 333 167 250 143 133 333 02011986225

045 035 100 111 059 080 056 050 125 00711986226

045 030 090 100 056 071 050 045 111 00611986227

080 060 170 180 100 133 083 080 200 01111986228

060 040 125 140 075 100 067 067 143 00911986229

090 070 180 200 120 150 100 091 222 01311986230

100 075 200 220 125 150 110 100 250 01411986231

040 030 080 090 050 070 045 040 100 006120582max = 900585 CI = 0000731 CR = 0000504 lt 01

Table 7 Judgment matrixes and weights of ldquonatural environmentriskrdquo criteria

Natural environment risk 11986232

11986233

Local weight11986232

1 18 06411986233

056 1 036120582max = 2 CI = 0 CR = 0 lt 01

444 Substep 4 Consistency Test The consistency of relativeimportance judgment on each indicator made by expertsand engineers is the key prerequisite for using the AHP todetermine the weights of risk indicators Hence it is verynecessary to test the consistency of judgment matrix Whenthe consistency of judgmentmatrix is satisfied themaximumeigenvalue of the judgmentmatrix120582max should be equal to thenumber of indicators which are related to two consistencytest indices namely CI and CR

Consistency index (CI) which measures the divergenceof judgment matrix away from the consistency is defined asfollows

CI =120582max minus 119899

119899 minus 1 (1)

where 119899 represents the number of indicesThus the consistency ratio (CR) is defined as follows

CR =CIRI

(2)

RI is the random consistency index which is the averagevalue of eigenvalues obtained by calculating the judgmentmatrix for more than 500 times The value of RI is given inTable 9

If CR lt 01 the weight vector is acceptable otherwisethe modification of the pairwise judgment matrix is needed

As listed in the last row in Tables 3ndash8 respectivelyall the pairwise comparison judgment matrixes satisfy theconsistency test

445 Substep 5 Calculate the Index Weight The globalweight of each indicator can be determined by multiplying

the local weight of the indicator with theweight of upper layerindicator which locates in the parent node above it

The local and global weights of each risk indicator inindex layer and the weight of each indicator in criteria layerare calculated which are listed in Table 10

45 Step 5 Calculate the Fuzzy Relation Matrix Accordingto the statistical result of the questionnaire by using a certainmathematical method such as frequency-based method andweighted averagemethod the first-level fuzzy relationmatrixR can be calculated as follows

R = (119903119894119895)119899times119898

=

[[[[

[

11990311

11990312

1199031119898

11990321

11990322

1199032119898

1199031198991

1199031198992

119903119899119898

]]]]

]

(3)

where 119903119894119895is the membership degree of the 119895th remark in

remark set V for the indicator 119894 119894 = 1 2 119899 119895 =

1 2 119898 119899 is the number of indices and 119898 is the numberof risk grades in remark set V Different rows in the fuzzyrelation matrix R reflect the different membership degrees ofevaluated object subject to fuzzy set of each grade consideringdifferent evaluation indices

The frequency-based method is used to establish thefuzzy relation matrix in this paper the principle of which isif the number of experts and engineers who judge the ldquohighriskrdquo ldquomoderate riskrdquo and ldquolow riskrdquo is119898

1 1198982 and119898

3respec-

tively then the set (1198981sum3

119896=1119898119896 1198982sum3

119896=1119898119896 1198983sum3

119896=1119898119896)

is the membership set of the evaluation index The obtainedfrequency of each indicator with different risk grades is listedin Figure 7

Thus the first-level fuzzy relation matrix R can becalculated just as follows

1198771=

[[[[[[[

[

01277 04574 04149

04255 03830 05745

02660 05745 01595

00426 05638 03936

01702 03192 05106

00213 03617 06170

]]]]]]]

]

10 Mathematical Problems in Engineering

1198772=

[[[[[[[[[[[[[[[[[[[[[[[[[[

[

00106 04362 05532

00957 04894 04149

01170 05532 03298

00957 03298 05745

00638 04681 04681

01489 03617 04894

01383 04894 03723

00745 04787 04468

01596 03723 04681

01170 06915 01915

00426 04574 05000

00851 03830 05319

00532 04681 04787

00426 04149 05425

00426 04574 05000

00213 05638 04149

]]]]]]]]]]]]]]]]]]]]]]]]]]

]

1198773=

[[[[[[[[[[[[

[

01170 04787 04043

02021 04149 03830

00638 04575 04787

00532 04255 05213

00851 07447 01702

00638 07766 01596

00851 08404 00745

00958 07340 01702

00532 03191 06277

]]]]]]]]]]]]

]

1198774= [

01702 04468 03830

00106 05213 04681]

1198775=

[[[[[[[

[

02447 05638 01915

00957 05000 04043

02340 04787 02872

01064 04894 04042

00957 04681 04362

00638 05532 03830

]]]]]]]

]

(4)

46 Step 6 Make Fuzzy Composition Synthesize the first-level fuzzy relation matrix R with the local weight 119882

119871 and

then the membership matrix 119861119894could be obtained which is

call the first-level fuzzy comprehensive evaluation matrix

119861119894= 119882119871o119877 = (119887

1198941 1198871198942 119887

119894119898) (5)

Due to the hierarchical structure of the evaluation indexsystem the second-level fuzzy relation matrix 119877

1015840 needs to becalculated

1198771015840=

[[[[

[

1198611

1198612

119861119896

]]]]

]

=[[[

[

11988711

11988712

sdot sdot sdot 1198871119898

11988721

11988722

sdot sdot sdot 1198872119898

sdot sdot sdot sdot sdot sdot sdot sdot sdot sdot sdot sdot

1198871198961

1198871198962

sdot sdot sdot 119887119896119898

]]]

]

(6)

Then combined with the weight matrix 119882 the second-level fuzzy comprehensive evaluation matrix B can be calcu-lated as follows

B = 119882o1198771015840 = (1198871 1198872 119887

119898) (7)

where 119887119898is the membership degree of the 119898th remark in

remark set VIn this paper the first-level fuzzy comprehensive evalua-

tion matrix 119861119894is calculated as follows

1198611= 1198821198711o1198771

= (020 007 037 008 022 006)

o

[[[[[[[

[

01277 04574 04149

04255 03830 05745

02660 05745 01595

00426 05638 03936

01702 03192 05106

00213 03617 06170

]]]]]]]

]

= (01690 04679 03631)

(8)

Similarly we can obtain

1198612= (01005 04585 04310)

1198613= (01073 05905 03022)

1198614= (01128 04736 04136)

1198615= (01710 05133 03157)

(9)

Then we obtain the second-level fuzzy relationmatrix1198771015840

1198771015840=

[[[[[

[

01690 04679 03631

01005 04585 04310

01073 05905 03022

01128 04736 04136

01710 05133 03157

]]]]]

]

(10)

The second-level fuzzy comprehensive evaluation matrixB can be calculated as follows

B = 119882o1198771015840

= (020 022 015 012 031)

o[[[[[

[

01690 04679 03631

01005 04585 04310

01073 05905 03022

01128 04736 04136

01710 05133 03157

]]]]]

]

= (01385 04990 03603)

(11)

47 Step 7 Rate and Conclude the Grade Level Accordingto the maximum membership degree principle when 119887

1198940=

max 119887119894(1 le 119894 le 119898) we can judge that the evaluated object

belongs to the 1198940grade

In this paper since 1198872

= max 119887119894(1 le 119894 le 3) =

04990 it is shown that the risk grade of ldquoZhejiang-FuzhourdquoUHV power transmission construction project belongs toldquomoderaterdquo which means the occurrence probability of thisproject risk is medium and the risk occurrence will causegeneral loss So it is necessary for the project managers to

Mathematical Problems in Engineering 11

Table 8 Judgment matrixes and weights of ldquosociety riskrdquo criteria

Society risk 11986234

11986235

11986236

11986237

11986238

11986239

Local weight11986234

1 23 12 18 2 3 02911986235

043 1 05 08 09 13 01211986236

083 2 1 15 17 25 02411986237

056 125 067 1 11 17 01611986238

05 011 059 091 1 15 01011986239

033 077 04 059 067 1 009120582max = 59109 CI = minus00178 CR = minus00141 lt 01

Table 9 The value of RI

119899 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15RI 0 052 089 112 126 136 141 145 149 152 154 156 157 158

carry out some specific risk control measures to make theconstruction of this project run successfully

At the meantime valuing the evaluation result of indi-cators in criteria layer in centesimal form can help projectmanagers to analyze the project riskmore efficiently Supposethe comment set V = [V

1 V2 V3] = 90 50 10 and then

the centesimal value of each indicator in criteria layer can becalculated as follows

1198801= 01690 times 90 + 04679 times 50 + 03631 times 10

= 422383

1198802= 01005 times 90 + 04585 times 50 + 04310 times 10

= 362830

1198803= 01073 times 90 + 05905 times 50 + 03022 times 10

= 422

1198804= 01128 times 90 + 04736 times 50 + 04136 times 10

= 379660

1198805= 01710 times 90 + 05133 times 50 + 03157 times 10

= 442085

(12)

The centesimal value (119880) of risk evaluation of ldquoZhejiang-Fuzhourdquo UHV power transmission construction project canbe calculated as

119880 = 01385 times 90 + 04990 times 50 + 03603 times 10

= 410205

(13)

Figure 8 compares the centesimal value of each indicatorin criteria layer and we can see

1198805≻ 1198801≻ 1198803≻ 119880 ≻ 119880

4≻ 1198802 (14)

Therefore the centesimal value of ldquosociety riskrdquo is thehighest followed by ldquopolicy and law riskrdquo ldquotechnology riskrdquoldquonatural environmental riskrdquo and ldquomanagement riskrdquo Thecentesimal values of both ldquomanagement riskrdquo and ldquonatural

422383

36283

422

37966

442085

Policy and law

Management

Technology

Natural environmental

Society

Centesimal value

Centesimal value of U

risk

risk

risk

risk

risk0 5 10 15 20 25 30 35 40 45 50

Figure 8 Centesimal value of each indicator in criteria layer

environmental riskrdquo are lower than that of the project119880 whilethe centesimal values of other three indicators are larger thanthat of the project 119880 The criteria ldquoSociety riskrdquo ldquopolicy andlaw riskrdquo and ldquotechnology riskrdquo should be paidmore attentionin the risk management and control for ldquoZhejiang-FuzhourdquoUHV power transmission construction project

5 Risk Control Recommendations

According to the risk evaluation result we should paymore attention to ldquosociety riskrdquo ldquopolicy and law riskrdquo andldquotechnology riskrdquoThe specific risk control recommendationsare as follows

51 Risk Control Recommendations for ldquoSociety Riskrdquo

(1) Before and during the construction of ldquoZhejiang-Fuzhourdquo UHV power transmission project the pro-paganda work should be done in the form of TVradio newspapers brochures and so on The con-struction significance and engineering safety knowl-edge related to this project should be propagandizedin order to eliminate the worries from society fol-lowers and local villagers about this UHV powertransmission project

12 Mathematical Problems in Engineering

Table 10 The weight of risk indicators

Criteria layer Index layerIndicator Weight (119882) Indicator Local weight (119882

119871) Global weight (119882

119866)

Policy and law risk (1198801) 020

1198621

020 004001198622

007 001401198623

037 007401198624

008 001601198625

022 004401198626

006 00120

Management risk (1198802) 022

1198627

003 000661198628

007 001541198629

009 0019811986210

006 0013211986211

004 0008811986212

011 0024211986213

009 0019811986214

006 0013211986215

012 0026411986216

009 0019811986217

003 0006611986218

005 0011011986219

004 0008811986220

004 0008811986221

004 0008811986222

003 00066

Technology risk (1198803) 015

11986223

014 0021011986224

020 0030011986225

007 0010511986226

006 0009011986227

011 0016511986228

009 0013511986229

013 0019511986230

014 0021011986231

006 00090

Natural environment risk (1198804) 012 119862

32064 00768

11986233

036 00432

Society risk (1198805) 031

11986234

029 0089911986235

012 0037211986236

024 0074411986237

016 0049611986238

01 0031011986239

009 00279

(2) Grid company should try to sign a contract withlocal government which strives to make the localgovernment be responsible for land requisition houserelocation and crop compensation Grid companycan also set up aworking group to coordinate with thelocal government The determination of land com-pensation standards not only abides by the relevantlaws and regulations but also takes the opinions oflocal masses into consideration

(3) The terrain and ecological resources along the projectline should be fully understood when selecting theoptimal route Having some experienced practition-ers on the team and considering the local customsare better for the route determination During theproject construction the water and soil loss as wellas deforestation should be reduced as far as possibleWhen the project is finished the vegetation should berestored timely

Mathematical Problems in Engineering 13

(4) Keep close touch with the local government andpublic security organization in order to strengthen thesecurity of project construction the ldquomass incidentsrdquosuch as petitions demagoguism and demonstrationshould be paid close attention and some relatedmeasures such as propaganda and negotiation shouldbe taken timely strengthen the project constructionmanagement and perform civilized construction andreduce the negative impacts on local residents to aminimum

52 Risk Control Recommendations for ldquoPolicy and Law Riskrdquo

(1) The project-related personnel especially the projectmanagers should carefully study the policies andlaws related to land management deforestation loanand environmental protection and the related legalcounsel should be engaged in order to reduce the legalrisk during the project construction

(2) Strengthen the research on the policies and guidancedocuments related to energy development and plan-ning

(3) Strengthen the communication with the governmentdepartment to improve the efficiency of project exam-ination and approval

(4) Because the size and weight of UHV equipment arebigger and heavier the traffic laws and regulationsshould be carefully studied to avoid the conflictrelated to UHV equipment transportation Trans-portation limitations should be taken into considera-tion when selecting the UHV equipment and surveyon the transport route is very necessary

53 Risk Control Recommendations for ldquoTechnology Riskrdquo

(1) Track the meteorological information timely andarrange the construction plan according to theweather condition some necessary measures shouldbe taken to protect the equipment from rainwatersuch as building the temporary drain and increasingthe pumping equipment

(2) The earth-rock excavation should keep a reasonableproportion based on the quantity calculation

(3) For waterway transport due to the constant changeof shipping lane the simulation navigation shouldbe performed six months in advance to ensure thetransportation safety

(4) Measure the earth resistivity and design the ground-ing grid establish special subjects to study the impactsof ground resistance on UHVGIS equipment and theoperation of control and protection system

(5) Design the crossing construction based on differ-ent crossing facilities to reduce the risk and diffi-culty when crossing the electricity lines the crossingscheme should be designed at the design stage and

take the terrain characteristic along the project lineinto consideration

(6) The material transport plan should take weather andtransportation environment into consideration opti-mize the use of different transportation facilities andmake the fullest use of crawler-transporter vehicleand cableway

6 Conclusions

In this paper a hybrid evaluation model based on AHPand FCE method is implemented to evaluate the risk ofldquoZhejiang-Fuzhourdquo UHV power transmission constructionprojectThis hybrid evaluationmodel takes full advantages ofAHP and FCEmethod After the risk evaluation index systemis built the AHP is used to determine the index weightand FCE method is used to evaluate the project risk Finallythe specific risk control recommendations are proposed Themain results of risk evaluation of ldquoZhejiang-Fuzhourdquo UHVpower transmission construction project are as follows

(1) The risk grade of ldquoZhejiang-Fuzhourdquo UHV powertransmission construction project belongs to ldquomod-eraterdquo which indicates the occurrence probability ofproject risk is medium and the risk occurrence willcause general loss

(2) ldquoSociety riskrdquo has the highest level and the next isldquopolicy and law riskrdquo ldquotechnique riskrdquo ldquonatural envi-ronmental riskrdquo and ldquomanagement riskrdquo respectivelyldquosociety riskrdquo ldquopolicy and law riskrdquo and ldquotechnologyriskrdquo should be paid more attention in the risk man-agement and control for ldquoZhejiang-Fuzhourdquo UHVpower transmission construction project

(3) Risk control recommendations for main risk criteriawhich include society risk policy and law risk andtechnology risk are proposed

(4) This hybrid evaluation model is feasible and effectivewhich can effectively evaluate the risk of UHV powertransmission construction project

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

This study is supported by the Humanity and Social Scienceproject of the Ministry of Education of China (Project no11YJA790217) and the National Natural Science Foundationof China (Project no 71373076)

References

[1] J P Liu D X Niu and X H Song ldquoThe energy supply anddemand pattern of China a review of evolution and sustainabledevelopmentrdquo Renewable and Sustainable Energy Reviews vol25 pp 220ndash228 2013

14 Mathematical Problems in Engineering

[2] C C Lin C H Yang and J Z Shyua ldquoA comparison ofinnovation policy in the smart grid industry across the pacificchina and the USArdquo Energy Policy vol 57 pp 119ndash132 2013

[3] M Bolinger and R Wiser ldquoA comparative analysis of businessstructures suitable for farmer-ownedwind power projects in theUnited Statesrdquo Energy Policy vol 34 no 14 pp 1750ndash1761 2006

[4] S Grassi N Chokani and R S Abhari ldquoLarge scale technicaland economical assessment of wind energy potential with a GIStool case study Iowardquo Energy Policy vol 45 pp 73ndash85 2012

[5] MHellstrom I Ruuska KWikstrom andD Jafs ldquoProject gov-ernance and path creation in the early stages of Finnish nuclearpower projectsrdquo International Journal of Project Managementvol 31 no 5 pp 712ndash723 2013

[6] P Baumann and G Stevanella ldquoFish passage principles to beconsidered for medium and large dams the case study of afish passage concept for a hydroelectric power project on theMekong mainstem in Laosrdquo Ecological Engineering vol 48 pp79ndash85 2012

[7] W Amatayakul and G Berndes ldquoDetermining factor for thedevelopment of CDM biomass power projectsrdquo Energy forSustainable Development vol 16 pp 197ndash203 2012

[8] J L Liu Q X Li and Y H Wang ldquoRisk analysis in ultradeep scientific drilling project-A fuzzy synthetic evaluationapproachrdquo International Journal of Project Management vol 31no 3 pp 449ndash458 2013

[9] A Badri S Nadeau and A Gbodossou ldquoA new practicalapproach to risk management for underground mining projectin Quebecrdquo Journal of Loss Prevention in the Process Industriesvol 26 no 6 pp 1145ndash1158 2013

[10] J B Song D R Song X Q Zhang and Y Sun ldquoRiskidentification for PPP waste-to-energy incineration projects inChinardquo Energy Policy vol 61 pp 953ndash962 2013

[11] Y Hu J F Du X Z Zhang et al ldquoAn integrative frameworkfor intelligent software project risk planningrdquo Decision SupportSystems vol 55 no 4 pp 927ndash937 2013

[12] T L Saaty The Analytic Hierarchy Process McGraw-Hill NewYork NY USA 1980

[13] M P Amiri ldquoProject selection for oil-fields development byusing the AHP and fuzzy TOPSIS methodsrdquo Expert Systemswith Applications vol 37 no 9 pp 6218ndash6224 2010

[14] H Z Li and S Guo ldquoExternal economies evaluation of windpower engineering project based on analytic hierarchy processand matter-element extension modelrdquo Mathematical Problemsin Engineering vol 2013 Article ID 848901 11 pages 2013

[15] F-G Chen H-L Yao andW-G Shi ldquoApplication of fuzzy andsynthetic judgment to risk assessment of dammed lakerdquo Journalof Shanghai Jiaotong University vol 45 no 1 pp 67ndash75 2011

[16] K Fang B-F He M Yang and Z-C Wang ldquoApplication offuzzy comprehensive evaluation method to CENSrdquo Journal ofHarbin Institute of Technology vol 43 no 5 pp 30ndash36 2011

Submit your manuscripts athttpwwwhindawicom

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mathematical Problems in Engineering

Hindawi Publishing Corporationhttpwwwhindawicom

Differential EquationsInternational Journal of

Volume 2014

Applied MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mathematical PhysicsAdvances in

Complex AnalysisJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

OptimizationJournal of

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CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Operations ResearchAdvances in

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Function Spaces

Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of Mathematics and Mathematical Sciences

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Algebra

Discrete Dynamics in Nature and Society

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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Decision SciencesAdvances in

Discrete MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom

Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Stochastic AnalysisInternational Journal of

4 Mathematical Problems in Engineering

the characteristics of selected risk indicators and the expertadvices these 39 risk indicators are divided into ldquopolicyand law riskrdquo ldquomanagement riskrdquo ldquotechnology riskrdquo ldquonaturalenvironment riskrdquo and ldquosociety riskrdquo which are called thefirst-level risk criteria Therefore the risk evaluation indexsystem of ldquoZhejiang-Fuzhourdquo UHV power transmission con-struction project is built just as shown in Figure 3 FromFigure 3 we can see that the risk evaluation index systemcontains 5 first-level risk criteria and 39 second-level riskindicators

4 Risk Evaluation on lsquolsquoZhejiang-FuzhoursquorsquoUHV Power Transmission ConstructionProject Based on AHP and FCM

Therisk evaluation on ldquoZhejiang-FuzhourdquoUHVpower trans-mission construction project targets the safe and smoothoperation of project Risk evaluation is the combinationof qualitative evaluation and quantitative evaluation Withregard to the UHV power transmission construction projectit is very hard to describe some risk factors with quantitativemethods precisely moreover some risk factors are valuedby experts with certain ambiguity Therefore the risk ofUHV power transmission construction project needs to beevaluated by using a certain fuzzy evaluationmethod In viewof this characteristic the fuzzy comprehensive evaluation(FCE) method is employed in this paper

Determining the weight of each risk indicator is a difficultbut crucial work when using FCEmethod to evaluate the riskof UHV power transmission construction project Whetherthe index weight value is reasonable or not is directly relatedto the reliability of risk evaluation result With regard tothe risk evaluation of UHV power transmission constructionproject it is a multiobjective issue that needs to considermany uncertain factors such as policy society and envi-ronment and so on meanwhile it also has a hierarchicalstructure Therefore the AHP method which can effectivelydeal with the issue with a hierarchical structure and considerthe wisdom and experience of expert to overcome theuncertain factors is selected to determine the risk indexweight

The AHP is a multiobjective decision-making tool com-bining qualitative and quantitative analysis [12] Its principleis as follows firstly divide the research issue into a hierarchi-cal structure based on the interrelationship and membershipbetween indicators secondly compare the importance ofeach indicator within the same layer with regard to theupper layer depending on the experience or intuition ofexperts thirdly obtain the importance of each indicatorwith regard to the final object through the hierarchicalstructure and use the consistency test to justify the resultaccuracy [13 14] The risk evaluation index system of UHVpower transmission construction project is such a systemthat contains a multilevel hierarchical structure and existscorrelation among indicators Therefore it is suitable to useAHP method to determine the weights of risk indicators

FCE method intended to quantify the vague factorswhich are difficult to quantify based on fuzzy mathematical

Table 1 The meaning of different risk types

Risk types Meaning

High risk The occurrence probability of project risk is greatand the risk occurrence will cause huge loss

Moderate riskThe occurrence probability of project risk ismedium and the risk occurrence will causegeneral loss

Low risk The occurrence probability of project risk is lowand the risk occurrence will cause small loss

method is a fuzzy bottom-up multicriteria decision making(MCDM) method [15 16] As a specific application of fuzzymathematics method FCE method was proposed by theChinese scholar P Z Wang Considering the various factorsassociated with the evaluation system the FCE method usesthe fuzzy linear transformation principle and maximummembership degree principle to quantify the fuzzy indicators

The framework of risk evaluation on ldquoZhejiang-FuzhourdquoUHV power transmission construction project based onAHP and FCMmethod is shown in Figure 4

The specific calculation steps for the risk evaluation onldquoZhejiang-Fuzhourdquo UHV power transmission constructionproject based on AHP and FCE method are as follows

41 Step 1 Building the Risk Evaluation Index System Theriskevaluation index system of ldquoZhejiang-Fuzhourdquo UHV powertransmission construction project has been built in Section 3just as shown in Figure 3

42 Step 2 Determine the Evaluated Object and EvaluationIndex Set For the evaluated object F the evaluation index set119862 = 119862

119894 (119894 = 1 2 119899) is an entiretywith intrinsic structure

composing of the indicators that represent the characteristicsof the evaluated object F

In this paper the evaluated object F is the risk ofldquoZhejiang-Fuzhourdquo UHV power transmission constructionproject The evaluation index set is composed of 39 riskindicators namely 119862 = 119862

119894 (119894 = 1 2 39)

43 Step 3 Give the Remark Set According to the evaluationstandard and grade the remark set V = [V

1 V2 V

119898] can

be made based on the opinions of experts and engineersconsidering the qualitative index and quantitative indextogether The remark set V is composed of different riskgrades and 119898 in the remark set V represents the number ofrisk grades

In this paper according to the characteristics ofldquoZhejiang-Fuzhourdquo UHV power transmission constructionproject and the expertise suggestion in the field of powergrid construction project the evaluated risk is divided intothree types namely ldquohigh riskrdquo ldquomoderate riskrdquo and ldquolowriskrdquo the meanings of which are listed in Table 1 Thus theremark set V can be made namely V = [V

1 V2 V3]

Mathematical Problems in Engineering 5

ldquoZhejiang-Fuzhourdquo

UHV power transmission construction

project

Policy and law risk

Technology risk

Society risk

Natural environmentrisk

Management risk

Project approval policy risk

Loan policy risk

Environmental protection law risk

Unsound traffic law risk

Adjustment risk on energy development strategyand electric planning policyLand requisition and logging policy risk

Quality management risk

Security management riskGoods and material management risk

Contract management risk

Bidding management risk

Project budget risk

Project design risk

Feasibility research risk

Other department coordination risk

Operation preparation riskCompletion inspection and approval risk

Debugging riskImmature contractor risk

Supervision risk

Investment risk

Schedule risk

Substation construction risk

Technical immature risk

Depopulated zone construction risk

Mountain material transportation risk

Tower construction risk

Important line crossing risk

Equipment installation risk

Grounding project resistance reduction risk

Large equipment transportation risk

Social and public opinion risk

Possible social risk due to immature regime

Life security concern risk

Maladjustment risk to the living environment changes

Possible ecological damage risk

Land requisition removing and crop compensation risk

Natural disaster risk

Adverse geological condition risk

Figure 3 The risk evaluation index system of ldquoZhejiang-Fuzhourdquo UHV power transmission construction project

6 Mathematical Problems in Engineering

Construct the hierarchical structure model

Construct the judgment matrixes

Determine the weight vector of risk index

Consistency test

Satisfied

Determine the evaluated object and evaluation index set

Give the remark set

Determine the index weight

Calculate the fuzzy relation matrix

Make fuzzy composition

Rate and conclude the grade level

AHP method to determine index weight

Nonsatisfied

Build the risk evaluation index system

Figure 4 The framework of risk evaluation

44 Step 4Determine the IndexWeight byUsingAHPMethodIn this paper the AHP method is employed to determinethe index weight After building the evaluation index systemthe local weight 119882

119871= 1199081198711

1199081198712

119908119871119899

and global weight119882119866

= 1199081198661

1199081198662

119908119866119899

of indicators in index layer andthe weight119882 = 119908

1 1199082 119908

ℎ of indicators in criteria layer

can be calculated where sum119899

119894=1119908119866119894

= 1 sumℎ119894=1

119908119894= 1 0 le 119908

119866119894

119908119894le 1

441 Substep 1 Construct the Hierarchical Structure ModelAccording to the overall goal and characteristics of MCDMproblem the complex determination of index weight isdecomposed and framed as a bottom-up hierarchical struc-ture which includes the goal layer criteria layer and indexlayer just as shown in Figure 5

In this paper the risk evaluation index system contains5 first-level risk criteria and 39 second-level risk indicatorsSuppose 119880 = 119880

1 1198802 1198803 1198804 1198805 = policy and law risk

management risk technology risk natural environment risksociety risks 119862 = 119862

1 1198622 119862

39 = project approval

policy risk adjustment risk on energy development strategyand electric planning policy land requisition and loggingpolicy risk social and public opinion risk The bottom-up hierarchical structure of risk evaluation of ldquoZhejiang-Fuzhourdquo UHV power transmission construction project isshown in Figure 6

Goal

Index

Criteria middot middot middot middot middot middot

middot middot middot middot middot middot middot middot middot

middot middot middot middot middot middot middot middot middot

Figure 5 The hierarchical structure of AHP for determining theindex weights

442 Substep 2 Construct the Judgment Matrixes The AHPuses the pairwise comparison method to construct thejudgmentmatrixes for both criteria layer and index layerThepairwise comparison is performed by using a nine-point scalewhich can convert human preference into quantitative valuejust as shown in Table 2

According to the analysis shown in Table 2 it shows that119886119894119895

gt 0 119886119894119894= 1 119886

119895119894= 1119886119894119895

In this paper after recognizing the judgments and opin-ions of experts and engineers related to UHV power trans-mission construction project according to the questionnaireresult the judgment matrixes of criteria layer and index layerby using the nine-point scale pair-wise comparison methodare constructed and the results are shown in Tables 3 4 5 67 and 8

Mathematical Problems in Engineering 7

Criteria

Risk evaluation of ldquoZhejiang-Fuzhourdquo UHV power transmission construction project

Policy and law risk Technology risk

Index

Management risk

Quality management risk

Security management risk

Goods and material management risk

Contract management risk

Bidding management risk

Project budget risk

Project design risk

Feasibility research risk

Other department coordination risk

Operation preparation risk

Completion inspection and approval risk

Debugging risk

Immature contractor risk

Supervision risk

Investment risk

Schedule risk

Project approval policy risk

Loan policy risk

Environmental protection law risk

Unsound traffic law risk

Adjustment risk on energy development strategy and electric

planning policy

Land requisition and logging policy risk

Substation construction risk

Technical immature risk

Depopulated zone construction risk

Mountain material transportation risk

Tower construction risk

Important line crossing risk

Equipment installation risk

Grounding projectresistance reduction risk

Large equipmenttransportation risk

Natural environment risk

Natural disaster

risk

Adverse geological condition

risk

Possible social risk due to immature

regime

Life security concern risk

Maladjustment risk to the living

environment changes

Possible ecological damage risk

Land requisition removing and crop compensation risk

Social and public opinion risk

Society risk

Goal

(C1)

(C2)

(C3)

(C4)

(C5)

(C6)

(C7)

(C8)

(C9)

(C10)

(C11)

(C12)

(C13)

(C14)

(C15)

(C16)

(C17)

(C18)

(C19)

(C20)

(C21)

(C22)

(C23)

(C24)

(C25)

(C26)

(C27)

(C28)

(C29)

(C30)

(C31)

(C32)

(C33)

(C34)

(C35)

(C36)

(C37)

(C38)

(C39)

(U1) (U2) (U3) (U4)(U5)

Figure 6 The hierarchical structure of risk evaluation

0

10

20

30

40

50

60

70

80

90

100

The o

btai

ned

frequ

ency

of e

ach

indi

cato

r

Risk indicator

C1

C3

C5

C7

C9

C11

C13

C15

C17

C19

C21

C23

C25

C27

C29

C31

C33

C35

C37

C39

High riskModerate riskLow risk

Figure 7 The obtained frequency of each indicator with differentrisk levels

Table 2 Nine-point comparison scale

Scale (119886119894119895) Meaning

1 Indicator 119909119894is of the same importance as indicator 119909

119895

3 Indicator 119909119894is slightly more important than indicator

119909119895

5 Indicator 119909119894is obviously more important than

indicator 119909119895

7 Indicator 119909119894is strongly more important than

indicator 119909119895

9 Indicator 119909119894is extremely more important than

indicator 119909119895

2 4 6 8 Middle value of aboveReciprocal 119909

119894119909119895= 119886119894119895 then 119909

119895119909119894= 119886119895119894

= 1119886119894119895

443 Substep 3 Determine the Weight Vector of Risk IndexAfter the judgment matrix is obtained the order weightvector of risk index can be calculated by using Eigenvalue

8 Mathematical Problems in Engineering

Table 3 Pairwise comparison judgment matrixes and weights in criteria layer

1198801

1198802

1198803

1198804

1198805

Weight1198801

100 090 140 180 065 0201198802

111 100 150 165 070 0221198803

071 067 100 125 045 0151198804

056 061 080 100 040 0121198805

154 143 222 250 100 031120582max = 50034 CI = 000084 CR = 000075 lt 01

Table 4 Judgment matrixes and weights of ldquopolicy and law riskrdquo criteria

Policy and law risk 1198621

1198622

1198623

1198624

1198625

1198626

Local weight1198621

100 300 050 250 080 350 0201198622

033 100 020 090 033 120 0071198623

200 500 100 450 200 520 0371198624

040 111 022 100 030 160 0081198625

125 300 050 333 100 320 0221198626

029 083 019 063 031 100 006120582max = 60297 CI = 00059 CR = 00048 lt 01

Table 5 Judgment matrixes and weights of ldquomanagement riskrdquo criteria

Managementrisk 119862

71198628

1198629

11986210

11986211

11986212

11986213

11986214

11986215

11986216

11986217

11986218

11986219

11986220

11986221

11986222 Local weight

1198627

100 033 029 050 067 025 028 050 024 028 091 056 077 083 083 091 003

1198628

300 100 091 120 150 067 071 130 040 067 250 180 200 220 230 250 007

1198629

350 110 100 150 250 083 100 150 083 100 250 200 260 280 280 300 009

11986210

200 083 067 100 120 050 056 100 045 067 150 120 150 160 160 180 006

11986211

150 067 040 083 100 033 045 077 029 040 130 083 110 120 120 130 004

11986212

400 150 120 200 300 100 120 180 083 120 320 200 280 300 300 320 011

11986213

360 140 100 180 220 083 100 160 083 100 280 180 220 230 230 250 009

11986214

200 077 067 100 130 056 063 100 050 056 180 110 150 160 160 180 006

11986215

420 250 120 220 350 120 120 200 100 120 400 220 300 320 320 350 012

11986216

360 150 100 150 250 083 100 180 083 100 250 180 220 240 240 250 009

11986217

110 040 040 067 077 031 036 056 025 040 100 067 083 091 091 100 003

11986218

180 056 050 083 120 050 056 091 045 056 150 100 150 160 160 180 005

11986219

130 050 038 067 091 036 045 067 033 045 120 067 100 120 120 110 004

11986220

120 045 036 063 083 033 043 063 031 042 110 063 083 100 100 110 004

11986221

120 043 036 063 083 033 043 063 031 042 110 063 083 100 100 110 004

11986222

110 04 033 056 077 031 040 056 029 040 100 056 091 091 091 100 003120582max = 16055 CI = 0003697 CR = 00023 lt 01

method The eigenvector of judgment matrix with the max-imum eigenvalue is the weight vector of risk index whichdenotes the relative importance of indicators in the same levelwith regard to the indicators in the upper layer The weightvector of risk index is the relative importance of indicators

with regard to the upper layer indicator which is also calledthe local weight

In this paper the weights of indictors in criteria layer andlocal weights of indicators in index layer are calculated whichare lists in Tables 3ndash8 respectively

Mathematical Problems in Engineering 9

Table 6 Judgment matrixes and weights of ldquotechnology riskrdquo criteria

Technology risk 11986223

11986224

11986225

11986226

11986227

11986228

11986229

11986230

11986231

Local weight11986223

100 067 222 222 125 167 111 100 250 01411986224

150 100 286 333 167 250 143 133 333 02011986225

045 035 100 111 059 080 056 050 125 00711986226

045 030 090 100 056 071 050 045 111 00611986227

080 060 170 180 100 133 083 080 200 01111986228

060 040 125 140 075 100 067 067 143 00911986229

090 070 180 200 120 150 100 091 222 01311986230

100 075 200 220 125 150 110 100 250 01411986231

040 030 080 090 050 070 045 040 100 006120582max = 900585 CI = 0000731 CR = 0000504 lt 01

Table 7 Judgment matrixes and weights of ldquonatural environmentriskrdquo criteria

Natural environment risk 11986232

11986233

Local weight11986232

1 18 06411986233

056 1 036120582max = 2 CI = 0 CR = 0 lt 01

444 Substep 4 Consistency Test The consistency of relativeimportance judgment on each indicator made by expertsand engineers is the key prerequisite for using the AHP todetermine the weights of risk indicators Hence it is verynecessary to test the consistency of judgment matrix Whenthe consistency of judgmentmatrix is satisfied themaximumeigenvalue of the judgmentmatrix120582max should be equal to thenumber of indicators which are related to two consistencytest indices namely CI and CR

Consistency index (CI) which measures the divergenceof judgment matrix away from the consistency is defined asfollows

CI =120582max minus 119899

119899 minus 1 (1)

where 119899 represents the number of indicesThus the consistency ratio (CR) is defined as follows

CR =CIRI

(2)

RI is the random consistency index which is the averagevalue of eigenvalues obtained by calculating the judgmentmatrix for more than 500 times The value of RI is given inTable 9

If CR lt 01 the weight vector is acceptable otherwisethe modification of the pairwise judgment matrix is needed

As listed in the last row in Tables 3ndash8 respectivelyall the pairwise comparison judgment matrixes satisfy theconsistency test

445 Substep 5 Calculate the Index Weight The globalweight of each indicator can be determined by multiplying

the local weight of the indicator with theweight of upper layerindicator which locates in the parent node above it

The local and global weights of each risk indicator inindex layer and the weight of each indicator in criteria layerare calculated which are listed in Table 10

45 Step 5 Calculate the Fuzzy Relation Matrix Accordingto the statistical result of the questionnaire by using a certainmathematical method such as frequency-based method andweighted averagemethod the first-level fuzzy relationmatrixR can be calculated as follows

R = (119903119894119895)119899times119898

=

[[[[

[

11990311

11990312

1199031119898

11990321

11990322

1199032119898

1199031198991

1199031198992

119903119899119898

]]]]

]

(3)

where 119903119894119895is the membership degree of the 119895th remark in

remark set V for the indicator 119894 119894 = 1 2 119899 119895 =

1 2 119898 119899 is the number of indices and 119898 is the numberof risk grades in remark set V Different rows in the fuzzyrelation matrix R reflect the different membership degrees ofevaluated object subject to fuzzy set of each grade consideringdifferent evaluation indices

The frequency-based method is used to establish thefuzzy relation matrix in this paper the principle of which isif the number of experts and engineers who judge the ldquohighriskrdquo ldquomoderate riskrdquo and ldquolow riskrdquo is119898

1 1198982 and119898

3respec-

tively then the set (1198981sum3

119896=1119898119896 1198982sum3

119896=1119898119896 1198983sum3

119896=1119898119896)

is the membership set of the evaluation index The obtainedfrequency of each indicator with different risk grades is listedin Figure 7

Thus the first-level fuzzy relation matrix R can becalculated just as follows

1198771=

[[[[[[[

[

01277 04574 04149

04255 03830 05745

02660 05745 01595

00426 05638 03936

01702 03192 05106

00213 03617 06170

]]]]]]]

]

10 Mathematical Problems in Engineering

1198772=

[[[[[[[[[[[[[[[[[[[[[[[[[[

[

00106 04362 05532

00957 04894 04149

01170 05532 03298

00957 03298 05745

00638 04681 04681

01489 03617 04894

01383 04894 03723

00745 04787 04468

01596 03723 04681

01170 06915 01915

00426 04574 05000

00851 03830 05319

00532 04681 04787

00426 04149 05425

00426 04574 05000

00213 05638 04149

]]]]]]]]]]]]]]]]]]]]]]]]]]

]

1198773=

[[[[[[[[[[[[

[

01170 04787 04043

02021 04149 03830

00638 04575 04787

00532 04255 05213

00851 07447 01702

00638 07766 01596

00851 08404 00745

00958 07340 01702

00532 03191 06277

]]]]]]]]]]]]

]

1198774= [

01702 04468 03830

00106 05213 04681]

1198775=

[[[[[[[

[

02447 05638 01915

00957 05000 04043

02340 04787 02872

01064 04894 04042

00957 04681 04362

00638 05532 03830

]]]]]]]

]

(4)

46 Step 6 Make Fuzzy Composition Synthesize the first-level fuzzy relation matrix R with the local weight 119882

119871 and

then the membership matrix 119861119894could be obtained which is

call the first-level fuzzy comprehensive evaluation matrix

119861119894= 119882119871o119877 = (119887

1198941 1198871198942 119887

119894119898) (5)

Due to the hierarchical structure of the evaluation indexsystem the second-level fuzzy relation matrix 119877

1015840 needs to becalculated

1198771015840=

[[[[

[

1198611

1198612

119861119896

]]]]

]

=[[[

[

11988711

11988712

sdot sdot sdot 1198871119898

11988721

11988722

sdot sdot sdot 1198872119898

sdot sdot sdot sdot sdot sdot sdot sdot sdot sdot sdot sdot

1198871198961

1198871198962

sdot sdot sdot 119887119896119898

]]]

]

(6)

Then combined with the weight matrix 119882 the second-level fuzzy comprehensive evaluation matrix B can be calcu-lated as follows

B = 119882o1198771015840 = (1198871 1198872 119887

119898) (7)

where 119887119898is the membership degree of the 119898th remark in

remark set VIn this paper the first-level fuzzy comprehensive evalua-

tion matrix 119861119894is calculated as follows

1198611= 1198821198711o1198771

= (020 007 037 008 022 006)

o

[[[[[[[

[

01277 04574 04149

04255 03830 05745

02660 05745 01595

00426 05638 03936

01702 03192 05106

00213 03617 06170

]]]]]]]

]

= (01690 04679 03631)

(8)

Similarly we can obtain

1198612= (01005 04585 04310)

1198613= (01073 05905 03022)

1198614= (01128 04736 04136)

1198615= (01710 05133 03157)

(9)

Then we obtain the second-level fuzzy relationmatrix1198771015840

1198771015840=

[[[[[

[

01690 04679 03631

01005 04585 04310

01073 05905 03022

01128 04736 04136

01710 05133 03157

]]]]]

]

(10)

The second-level fuzzy comprehensive evaluation matrixB can be calculated as follows

B = 119882o1198771015840

= (020 022 015 012 031)

o[[[[[

[

01690 04679 03631

01005 04585 04310

01073 05905 03022

01128 04736 04136

01710 05133 03157

]]]]]

]

= (01385 04990 03603)

(11)

47 Step 7 Rate and Conclude the Grade Level Accordingto the maximum membership degree principle when 119887

1198940=

max 119887119894(1 le 119894 le 119898) we can judge that the evaluated object

belongs to the 1198940grade

In this paper since 1198872

= max 119887119894(1 le 119894 le 3) =

04990 it is shown that the risk grade of ldquoZhejiang-FuzhourdquoUHV power transmission construction project belongs toldquomoderaterdquo which means the occurrence probability of thisproject risk is medium and the risk occurrence will causegeneral loss So it is necessary for the project managers to

Mathematical Problems in Engineering 11

Table 8 Judgment matrixes and weights of ldquosociety riskrdquo criteria

Society risk 11986234

11986235

11986236

11986237

11986238

11986239

Local weight11986234

1 23 12 18 2 3 02911986235

043 1 05 08 09 13 01211986236

083 2 1 15 17 25 02411986237

056 125 067 1 11 17 01611986238

05 011 059 091 1 15 01011986239

033 077 04 059 067 1 009120582max = 59109 CI = minus00178 CR = minus00141 lt 01

Table 9 The value of RI

119899 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15RI 0 052 089 112 126 136 141 145 149 152 154 156 157 158

carry out some specific risk control measures to make theconstruction of this project run successfully

At the meantime valuing the evaluation result of indi-cators in criteria layer in centesimal form can help projectmanagers to analyze the project riskmore efficiently Supposethe comment set V = [V

1 V2 V3] = 90 50 10 and then

the centesimal value of each indicator in criteria layer can becalculated as follows

1198801= 01690 times 90 + 04679 times 50 + 03631 times 10

= 422383

1198802= 01005 times 90 + 04585 times 50 + 04310 times 10

= 362830

1198803= 01073 times 90 + 05905 times 50 + 03022 times 10

= 422

1198804= 01128 times 90 + 04736 times 50 + 04136 times 10

= 379660

1198805= 01710 times 90 + 05133 times 50 + 03157 times 10

= 442085

(12)

The centesimal value (119880) of risk evaluation of ldquoZhejiang-Fuzhourdquo UHV power transmission construction project canbe calculated as

119880 = 01385 times 90 + 04990 times 50 + 03603 times 10

= 410205

(13)

Figure 8 compares the centesimal value of each indicatorin criteria layer and we can see

1198805≻ 1198801≻ 1198803≻ 119880 ≻ 119880

4≻ 1198802 (14)

Therefore the centesimal value of ldquosociety riskrdquo is thehighest followed by ldquopolicy and law riskrdquo ldquotechnology riskrdquoldquonatural environmental riskrdquo and ldquomanagement riskrdquo Thecentesimal values of both ldquomanagement riskrdquo and ldquonatural

422383

36283

422

37966

442085

Policy and law

Management

Technology

Natural environmental

Society

Centesimal value

Centesimal value of U

risk

risk

risk

risk

risk0 5 10 15 20 25 30 35 40 45 50

Figure 8 Centesimal value of each indicator in criteria layer

environmental riskrdquo are lower than that of the project119880 whilethe centesimal values of other three indicators are larger thanthat of the project 119880 The criteria ldquoSociety riskrdquo ldquopolicy andlaw riskrdquo and ldquotechnology riskrdquo should be paidmore attentionin the risk management and control for ldquoZhejiang-FuzhourdquoUHV power transmission construction project

5 Risk Control Recommendations

According to the risk evaluation result we should paymore attention to ldquosociety riskrdquo ldquopolicy and law riskrdquo andldquotechnology riskrdquoThe specific risk control recommendationsare as follows

51 Risk Control Recommendations for ldquoSociety Riskrdquo

(1) Before and during the construction of ldquoZhejiang-Fuzhourdquo UHV power transmission project the pro-paganda work should be done in the form of TVradio newspapers brochures and so on The con-struction significance and engineering safety knowl-edge related to this project should be propagandizedin order to eliminate the worries from society fol-lowers and local villagers about this UHV powertransmission project

12 Mathematical Problems in Engineering

Table 10 The weight of risk indicators

Criteria layer Index layerIndicator Weight (119882) Indicator Local weight (119882

119871) Global weight (119882

119866)

Policy and law risk (1198801) 020

1198621

020 004001198622

007 001401198623

037 007401198624

008 001601198625

022 004401198626

006 00120

Management risk (1198802) 022

1198627

003 000661198628

007 001541198629

009 0019811986210

006 0013211986211

004 0008811986212

011 0024211986213

009 0019811986214

006 0013211986215

012 0026411986216

009 0019811986217

003 0006611986218

005 0011011986219

004 0008811986220

004 0008811986221

004 0008811986222

003 00066

Technology risk (1198803) 015

11986223

014 0021011986224

020 0030011986225

007 0010511986226

006 0009011986227

011 0016511986228

009 0013511986229

013 0019511986230

014 0021011986231

006 00090

Natural environment risk (1198804) 012 119862

32064 00768

11986233

036 00432

Society risk (1198805) 031

11986234

029 0089911986235

012 0037211986236

024 0074411986237

016 0049611986238

01 0031011986239

009 00279

(2) Grid company should try to sign a contract withlocal government which strives to make the localgovernment be responsible for land requisition houserelocation and crop compensation Grid companycan also set up aworking group to coordinate with thelocal government The determination of land com-pensation standards not only abides by the relevantlaws and regulations but also takes the opinions oflocal masses into consideration

(3) The terrain and ecological resources along the projectline should be fully understood when selecting theoptimal route Having some experienced practition-ers on the team and considering the local customsare better for the route determination During theproject construction the water and soil loss as wellas deforestation should be reduced as far as possibleWhen the project is finished the vegetation should berestored timely

Mathematical Problems in Engineering 13

(4) Keep close touch with the local government andpublic security organization in order to strengthen thesecurity of project construction the ldquomass incidentsrdquosuch as petitions demagoguism and demonstrationshould be paid close attention and some relatedmeasures such as propaganda and negotiation shouldbe taken timely strengthen the project constructionmanagement and perform civilized construction andreduce the negative impacts on local residents to aminimum

52 Risk Control Recommendations for ldquoPolicy and Law Riskrdquo

(1) The project-related personnel especially the projectmanagers should carefully study the policies andlaws related to land management deforestation loanand environmental protection and the related legalcounsel should be engaged in order to reduce the legalrisk during the project construction

(2) Strengthen the research on the policies and guidancedocuments related to energy development and plan-ning

(3) Strengthen the communication with the governmentdepartment to improve the efficiency of project exam-ination and approval

(4) Because the size and weight of UHV equipment arebigger and heavier the traffic laws and regulationsshould be carefully studied to avoid the conflictrelated to UHV equipment transportation Trans-portation limitations should be taken into considera-tion when selecting the UHV equipment and surveyon the transport route is very necessary

53 Risk Control Recommendations for ldquoTechnology Riskrdquo

(1) Track the meteorological information timely andarrange the construction plan according to theweather condition some necessary measures shouldbe taken to protect the equipment from rainwatersuch as building the temporary drain and increasingthe pumping equipment

(2) The earth-rock excavation should keep a reasonableproportion based on the quantity calculation

(3) For waterway transport due to the constant changeof shipping lane the simulation navigation shouldbe performed six months in advance to ensure thetransportation safety

(4) Measure the earth resistivity and design the ground-ing grid establish special subjects to study the impactsof ground resistance on UHVGIS equipment and theoperation of control and protection system

(5) Design the crossing construction based on differ-ent crossing facilities to reduce the risk and diffi-culty when crossing the electricity lines the crossingscheme should be designed at the design stage and

take the terrain characteristic along the project lineinto consideration

(6) The material transport plan should take weather andtransportation environment into consideration opti-mize the use of different transportation facilities andmake the fullest use of crawler-transporter vehicleand cableway

6 Conclusions

In this paper a hybrid evaluation model based on AHPand FCE method is implemented to evaluate the risk ofldquoZhejiang-Fuzhourdquo UHV power transmission constructionprojectThis hybrid evaluationmodel takes full advantages ofAHP and FCEmethod After the risk evaluation index systemis built the AHP is used to determine the index weightand FCE method is used to evaluate the project risk Finallythe specific risk control recommendations are proposed Themain results of risk evaluation of ldquoZhejiang-Fuzhourdquo UHVpower transmission construction project are as follows

(1) The risk grade of ldquoZhejiang-Fuzhourdquo UHV powertransmission construction project belongs to ldquomod-eraterdquo which indicates the occurrence probability ofproject risk is medium and the risk occurrence willcause general loss

(2) ldquoSociety riskrdquo has the highest level and the next isldquopolicy and law riskrdquo ldquotechnique riskrdquo ldquonatural envi-ronmental riskrdquo and ldquomanagement riskrdquo respectivelyldquosociety riskrdquo ldquopolicy and law riskrdquo and ldquotechnologyriskrdquo should be paid more attention in the risk man-agement and control for ldquoZhejiang-Fuzhourdquo UHVpower transmission construction project

(3) Risk control recommendations for main risk criteriawhich include society risk policy and law risk andtechnology risk are proposed

(4) This hybrid evaluation model is feasible and effectivewhich can effectively evaluate the risk of UHV powertransmission construction project

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

This study is supported by the Humanity and Social Scienceproject of the Ministry of Education of China (Project no11YJA790217) and the National Natural Science Foundationof China (Project no 71373076)

References

[1] J P Liu D X Niu and X H Song ldquoThe energy supply anddemand pattern of China a review of evolution and sustainabledevelopmentrdquo Renewable and Sustainable Energy Reviews vol25 pp 220ndash228 2013

14 Mathematical Problems in Engineering

[2] C C Lin C H Yang and J Z Shyua ldquoA comparison ofinnovation policy in the smart grid industry across the pacificchina and the USArdquo Energy Policy vol 57 pp 119ndash132 2013

[3] M Bolinger and R Wiser ldquoA comparative analysis of businessstructures suitable for farmer-ownedwind power projects in theUnited Statesrdquo Energy Policy vol 34 no 14 pp 1750ndash1761 2006

[4] S Grassi N Chokani and R S Abhari ldquoLarge scale technicaland economical assessment of wind energy potential with a GIStool case study Iowardquo Energy Policy vol 45 pp 73ndash85 2012

[5] MHellstrom I Ruuska KWikstrom andD Jafs ldquoProject gov-ernance and path creation in the early stages of Finnish nuclearpower projectsrdquo International Journal of Project Managementvol 31 no 5 pp 712ndash723 2013

[6] P Baumann and G Stevanella ldquoFish passage principles to beconsidered for medium and large dams the case study of afish passage concept for a hydroelectric power project on theMekong mainstem in Laosrdquo Ecological Engineering vol 48 pp79ndash85 2012

[7] W Amatayakul and G Berndes ldquoDetermining factor for thedevelopment of CDM biomass power projectsrdquo Energy forSustainable Development vol 16 pp 197ndash203 2012

[8] J L Liu Q X Li and Y H Wang ldquoRisk analysis in ultradeep scientific drilling project-A fuzzy synthetic evaluationapproachrdquo International Journal of Project Management vol 31no 3 pp 449ndash458 2013

[9] A Badri S Nadeau and A Gbodossou ldquoA new practicalapproach to risk management for underground mining projectin Quebecrdquo Journal of Loss Prevention in the Process Industriesvol 26 no 6 pp 1145ndash1158 2013

[10] J B Song D R Song X Q Zhang and Y Sun ldquoRiskidentification for PPP waste-to-energy incineration projects inChinardquo Energy Policy vol 61 pp 953ndash962 2013

[11] Y Hu J F Du X Z Zhang et al ldquoAn integrative frameworkfor intelligent software project risk planningrdquo Decision SupportSystems vol 55 no 4 pp 927ndash937 2013

[12] T L Saaty The Analytic Hierarchy Process McGraw-Hill NewYork NY USA 1980

[13] M P Amiri ldquoProject selection for oil-fields development byusing the AHP and fuzzy TOPSIS methodsrdquo Expert Systemswith Applications vol 37 no 9 pp 6218ndash6224 2010

[14] H Z Li and S Guo ldquoExternal economies evaluation of windpower engineering project based on analytic hierarchy processand matter-element extension modelrdquo Mathematical Problemsin Engineering vol 2013 Article ID 848901 11 pages 2013

[15] F-G Chen H-L Yao andW-G Shi ldquoApplication of fuzzy andsynthetic judgment to risk assessment of dammed lakerdquo Journalof Shanghai Jiaotong University vol 45 no 1 pp 67ndash75 2011

[16] K Fang B-F He M Yang and Z-C Wang ldquoApplication offuzzy comprehensive evaluation method to CENSrdquo Journal ofHarbin Institute of Technology vol 43 no 5 pp 30ndash36 2011

Submit your manuscripts athttpwwwhindawicom

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mathematical Problems in Engineering

Hindawi Publishing Corporationhttpwwwhindawicom

Differential EquationsInternational Journal of

Volume 2014

Applied MathematicsJournal of

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CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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Function Spaces

Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of Mathematics and Mathematical Sciences

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Decision SciencesAdvances in

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Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Stochastic AnalysisInternational Journal of

Mathematical Problems in Engineering 5

ldquoZhejiang-Fuzhourdquo

UHV power transmission construction

project

Policy and law risk

Technology risk

Society risk

Natural environmentrisk

Management risk

Project approval policy risk

Loan policy risk

Environmental protection law risk

Unsound traffic law risk

Adjustment risk on energy development strategyand electric planning policyLand requisition and logging policy risk

Quality management risk

Security management riskGoods and material management risk

Contract management risk

Bidding management risk

Project budget risk

Project design risk

Feasibility research risk

Other department coordination risk

Operation preparation riskCompletion inspection and approval risk

Debugging riskImmature contractor risk

Supervision risk

Investment risk

Schedule risk

Substation construction risk

Technical immature risk

Depopulated zone construction risk

Mountain material transportation risk

Tower construction risk

Important line crossing risk

Equipment installation risk

Grounding project resistance reduction risk

Large equipment transportation risk

Social and public opinion risk

Possible social risk due to immature regime

Life security concern risk

Maladjustment risk to the living environment changes

Possible ecological damage risk

Land requisition removing and crop compensation risk

Natural disaster risk

Adverse geological condition risk

Figure 3 The risk evaluation index system of ldquoZhejiang-Fuzhourdquo UHV power transmission construction project

6 Mathematical Problems in Engineering

Construct the hierarchical structure model

Construct the judgment matrixes

Determine the weight vector of risk index

Consistency test

Satisfied

Determine the evaluated object and evaluation index set

Give the remark set

Determine the index weight

Calculate the fuzzy relation matrix

Make fuzzy composition

Rate and conclude the grade level

AHP method to determine index weight

Nonsatisfied

Build the risk evaluation index system

Figure 4 The framework of risk evaluation

44 Step 4Determine the IndexWeight byUsingAHPMethodIn this paper the AHP method is employed to determinethe index weight After building the evaluation index systemthe local weight 119882

119871= 1199081198711

1199081198712

119908119871119899

and global weight119882119866

= 1199081198661

1199081198662

119908119866119899

of indicators in index layer andthe weight119882 = 119908

1 1199082 119908

ℎ of indicators in criteria layer

can be calculated where sum119899

119894=1119908119866119894

= 1 sumℎ119894=1

119908119894= 1 0 le 119908

119866119894

119908119894le 1

441 Substep 1 Construct the Hierarchical Structure ModelAccording to the overall goal and characteristics of MCDMproblem the complex determination of index weight isdecomposed and framed as a bottom-up hierarchical struc-ture which includes the goal layer criteria layer and indexlayer just as shown in Figure 5

In this paper the risk evaluation index system contains5 first-level risk criteria and 39 second-level risk indicatorsSuppose 119880 = 119880

1 1198802 1198803 1198804 1198805 = policy and law risk

management risk technology risk natural environment risksociety risks 119862 = 119862

1 1198622 119862

39 = project approval

policy risk adjustment risk on energy development strategyand electric planning policy land requisition and loggingpolicy risk social and public opinion risk The bottom-up hierarchical structure of risk evaluation of ldquoZhejiang-Fuzhourdquo UHV power transmission construction project isshown in Figure 6

Goal

Index

Criteria middot middot middot middot middot middot

middot middot middot middot middot middot middot middot middot

middot middot middot middot middot middot middot middot middot

Figure 5 The hierarchical structure of AHP for determining theindex weights

442 Substep 2 Construct the Judgment Matrixes The AHPuses the pairwise comparison method to construct thejudgmentmatrixes for both criteria layer and index layerThepairwise comparison is performed by using a nine-point scalewhich can convert human preference into quantitative valuejust as shown in Table 2

According to the analysis shown in Table 2 it shows that119886119894119895

gt 0 119886119894119894= 1 119886

119895119894= 1119886119894119895

In this paper after recognizing the judgments and opin-ions of experts and engineers related to UHV power trans-mission construction project according to the questionnaireresult the judgment matrixes of criteria layer and index layerby using the nine-point scale pair-wise comparison methodare constructed and the results are shown in Tables 3 4 5 67 and 8

Mathematical Problems in Engineering 7

Criteria

Risk evaluation of ldquoZhejiang-Fuzhourdquo UHV power transmission construction project

Policy and law risk Technology risk

Index

Management risk

Quality management risk

Security management risk

Goods and material management risk

Contract management risk

Bidding management risk

Project budget risk

Project design risk

Feasibility research risk

Other department coordination risk

Operation preparation risk

Completion inspection and approval risk

Debugging risk

Immature contractor risk

Supervision risk

Investment risk

Schedule risk

Project approval policy risk

Loan policy risk

Environmental protection law risk

Unsound traffic law risk

Adjustment risk on energy development strategy and electric

planning policy

Land requisition and logging policy risk

Substation construction risk

Technical immature risk

Depopulated zone construction risk

Mountain material transportation risk

Tower construction risk

Important line crossing risk

Equipment installation risk

Grounding projectresistance reduction risk

Large equipmenttransportation risk

Natural environment risk

Natural disaster

risk

Adverse geological condition

risk

Possible social risk due to immature

regime

Life security concern risk

Maladjustment risk to the living

environment changes

Possible ecological damage risk

Land requisition removing and crop compensation risk

Social and public opinion risk

Society risk

Goal

(C1)

(C2)

(C3)

(C4)

(C5)

(C6)

(C7)

(C8)

(C9)

(C10)

(C11)

(C12)

(C13)

(C14)

(C15)

(C16)

(C17)

(C18)

(C19)

(C20)

(C21)

(C22)

(C23)

(C24)

(C25)

(C26)

(C27)

(C28)

(C29)

(C30)

(C31)

(C32)

(C33)

(C34)

(C35)

(C36)

(C37)

(C38)

(C39)

(U1) (U2) (U3) (U4)(U5)

Figure 6 The hierarchical structure of risk evaluation

0

10

20

30

40

50

60

70

80

90

100

The o

btai

ned

frequ

ency

of e

ach

indi

cato

r

Risk indicator

C1

C3

C5

C7

C9

C11

C13

C15

C17

C19

C21

C23

C25

C27

C29

C31

C33

C35

C37

C39

High riskModerate riskLow risk

Figure 7 The obtained frequency of each indicator with differentrisk levels

Table 2 Nine-point comparison scale

Scale (119886119894119895) Meaning

1 Indicator 119909119894is of the same importance as indicator 119909

119895

3 Indicator 119909119894is slightly more important than indicator

119909119895

5 Indicator 119909119894is obviously more important than

indicator 119909119895

7 Indicator 119909119894is strongly more important than

indicator 119909119895

9 Indicator 119909119894is extremely more important than

indicator 119909119895

2 4 6 8 Middle value of aboveReciprocal 119909

119894119909119895= 119886119894119895 then 119909

119895119909119894= 119886119895119894

= 1119886119894119895

443 Substep 3 Determine the Weight Vector of Risk IndexAfter the judgment matrix is obtained the order weightvector of risk index can be calculated by using Eigenvalue

8 Mathematical Problems in Engineering

Table 3 Pairwise comparison judgment matrixes and weights in criteria layer

1198801

1198802

1198803

1198804

1198805

Weight1198801

100 090 140 180 065 0201198802

111 100 150 165 070 0221198803

071 067 100 125 045 0151198804

056 061 080 100 040 0121198805

154 143 222 250 100 031120582max = 50034 CI = 000084 CR = 000075 lt 01

Table 4 Judgment matrixes and weights of ldquopolicy and law riskrdquo criteria

Policy and law risk 1198621

1198622

1198623

1198624

1198625

1198626

Local weight1198621

100 300 050 250 080 350 0201198622

033 100 020 090 033 120 0071198623

200 500 100 450 200 520 0371198624

040 111 022 100 030 160 0081198625

125 300 050 333 100 320 0221198626

029 083 019 063 031 100 006120582max = 60297 CI = 00059 CR = 00048 lt 01

Table 5 Judgment matrixes and weights of ldquomanagement riskrdquo criteria

Managementrisk 119862

71198628

1198629

11986210

11986211

11986212

11986213

11986214

11986215

11986216

11986217

11986218

11986219

11986220

11986221

11986222 Local weight

1198627

100 033 029 050 067 025 028 050 024 028 091 056 077 083 083 091 003

1198628

300 100 091 120 150 067 071 130 040 067 250 180 200 220 230 250 007

1198629

350 110 100 150 250 083 100 150 083 100 250 200 260 280 280 300 009

11986210

200 083 067 100 120 050 056 100 045 067 150 120 150 160 160 180 006

11986211

150 067 040 083 100 033 045 077 029 040 130 083 110 120 120 130 004

11986212

400 150 120 200 300 100 120 180 083 120 320 200 280 300 300 320 011

11986213

360 140 100 180 220 083 100 160 083 100 280 180 220 230 230 250 009

11986214

200 077 067 100 130 056 063 100 050 056 180 110 150 160 160 180 006

11986215

420 250 120 220 350 120 120 200 100 120 400 220 300 320 320 350 012

11986216

360 150 100 150 250 083 100 180 083 100 250 180 220 240 240 250 009

11986217

110 040 040 067 077 031 036 056 025 040 100 067 083 091 091 100 003

11986218

180 056 050 083 120 050 056 091 045 056 150 100 150 160 160 180 005

11986219

130 050 038 067 091 036 045 067 033 045 120 067 100 120 120 110 004

11986220

120 045 036 063 083 033 043 063 031 042 110 063 083 100 100 110 004

11986221

120 043 036 063 083 033 043 063 031 042 110 063 083 100 100 110 004

11986222

110 04 033 056 077 031 040 056 029 040 100 056 091 091 091 100 003120582max = 16055 CI = 0003697 CR = 00023 lt 01

method The eigenvector of judgment matrix with the max-imum eigenvalue is the weight vector of risk index whichdenotes the relative importance of indicators in the same levelwith regard to the indicators in the upper layer The weightvector of risk index is the relative importance of indicators

with regard to the upper layer indicator which is also calledthe local weight

In this paper the weights of indictors in criteria layer andlocal weights of indicators in index layer are calculated whichare lists in Tables 3ndash8 respectively

Mathematical Problems in Engineering 9

Table 6 Judgment matrixes and weights of ldquotechnology riskrdquo criteria

Technology risk 11986223

11986224

11986225

11986226

11986227

11986228

11986229

11986230

11986231

Local weight11986223

100 067 222 222 125 167 111 100 250 01411986224

150 100 286 333 167 250 143 133 333 02011986225

045 035 100 111 059 080 056 050 125 00711986226

045 030 090 100 056 071 050 045 111 00611986227

080 060 170 180 100 133 083 080 200 01111986228

060 040 125 140 075 100 067 067 143 00911986229

090 070 180 200 120 150 100 091 222 01311986230

100 075 200 220 125 150 110 100 250 01411986231

040 030 080 090 050 070 045 040 100 006120582max = 900585 CI = 0000731 CR = 0000504 lt 01

Table 7 Judgment matrixes and weights of ldquonatural environmentriskrdquo criteria

Natural environment risk 11986232

11986233

Local weight11986232

1 18 06411986233

056 1 036120582max = 2 CI = 0 CR = 0 lt 01

444 Substep 4 Consistency Test The consistency of relativeimportance judgment on each indicator made by expertsand engineers is the key prerequisite for using the AHP todetermine the weights of risk indicators Hence it is verynecessary to test the consistency of judgment matrix Whenthe consistency of judgmentmatrix is satisfied themaximumeigenvalue of the judgmentmatrix120582max should be equal to thenumber of indicators which are related to two consistencytest indices namely CI and CR

Consistency index (CI) which measures the divergenceof judgment matrix away from the consistency is defined asfollows

CI =120582max minus 119899

119899 minus 1 (1)

where 119899 represents the number of indicesThus the consistency ratio (CR) is defined as follows

CR =CIRI

(2)

RI is the random consistency index which is the averagevalue of eigenvalues obtained by calculating the judgmentmatrix for more than 500 times The value of RI is given inTable 9

If CR lt 01 the weight vector is acceptable otherwisethe modification of the pairwise judgment matrix is needed

As listed in the last row in Tables 3ndash8 respectivelyall the pairwise comparison judgment matrixes satisfy theconsistency test

445 Substep 5 Calculate the Index Weight The globalweight of each indicator can be determined by multiplying

the local weight of the indicator with theweight of upper layerindicator which locates in the parent node above it

The local and global weights of each risk indicator inindex layer and the weight of each indicator in criteria layerare calculated which are listed in Table 10

45 Step 5 Calculate the Fuzzy Relation Matrix Accordingto the statistical result of the questionnaire by using a certainmathematical method such as frequency-based method andweighted averagemethod the first-level fuzzy relationmatrixR can be calculated as follows

R = (119903119894119895)119899times119898

=

[[[[

[

11990311

11990312

1199031119898

11990321

11990322

1199032119898

1199031198991

1199031198992

119903119899119898

]]]]

]

(3)

where 119903119894119895is the membership degree of the 119895th remark in

remark set V for the indicator 119894 119894 = 1 2 119899 119895 =

1 2 119898 119899 is the number of indices and 119898 is the numberof risk grades in remark set V Different rows in the fuzzyrelation matrix R reflect the different membership degrees ofevaluated object subject to fuzzy set of each grade consideringdifferent evaluation indices

The frequency-based method is used to establish thefuzzy relation matrix in this paper the principle of which isif the number of experts and engineers who judge the ldquohighriskrdquo ldquomoderate riskrdquo and ldquolow riskrdquo is119898

1 1198982 and119898

3respec-

tively then the set (1198981sum3

119896=1119898119896 1198982sum3

119896=1119898119896 1198983sum3

119896=1119898119896)

is the membership set of the evaluation index The obtainedfrequency of each indicator with different risk grades is listedin Figure 7

Thus the first-level fuzzy relation matrix R can becalculated just as follows

1198771=

[[[[[[[

[

01277 04574 04149

04255 03830 05745

02660 05745 01595

00426 05638 03936

01702 03192 05106

00213 03617 06170

]]]]]]]

]

10 Mathematical Problems in Engineering

1198772=

[[[[[[[[[[[[[[[[[[[[[[[[[[

[

00106 04362 05532

00957 04894 04149

01170 05532 03298

00957 03298 05745

00638 04681 04681

01489 03617 04894

01383 04894 03723

00745 04787 04468

01596 03723 04681

01170 06915 01915

00426 04574 05000

00851 03830 05319

00532 04681 04787

00426 04149 05425

00426 04574 05000

00213 05638 04149

]]]]]]]]]]]]]]]]]]]]]]]]]]

]

1198773=

[[[[[[[[[[[[

[

01170 04787 04043

02021 04149 03830

00638 04575 04787

00532 04255 05213

00851 07447 01702

00638 07766 01596

00851 08404 00745

00958 07340 01702

00532 03191 06277

]]]]]]]]]]]]

]

1198774= [

01702 04468 03830

00106 05213 04681]

1198775=

[[[[[[[

[

02447 05638 01915

00957 05000 04043

02340 04787 02872

01064 04894 04042

00957 04681 04362

00638 05532 03830

]]]]]]]

]

(4)

46 Step 6 Make Fuzzy Composition Synthesize the first-level fuzzy relation matrix R with the local weight 119882

119871 and

then the membership matrix 119861119894could be obtained which is

call the first-level fuzzy comprehensive evaluation matrix

119861119894= 119882119871o119877 = (119887

1198941 1198871198942 119887

119894119898) (5)

Due to the hierarchical structure of the evaluation indexsystem the second-level fuzzy relation matrix 119877

1015840 needs to becalculated

1198771015840=

[[[[

[

1198611

1198612

119861119896

]]]]

]

=[[[

[

11988711

11988712

sdot sdot sdot 1198871119898

11988721

11988722

sdot sdot sdot 1198872119898

sdot sdot sdot sdot sdot sdot sdot sdot sdot sdot sdot sdot

1198871198961

1198871198962

sdot sdot sdot 119887119896119898

]]]

]

(6)

Then combined with the weight matrix 119882 the second-level fuzzy comprehensive evaluation matrix B can be calcu-lated as follows

B = 119882o1198771015840 = (1198871 1198872 119887

119898) (7)

where 119887119898is the membership degree of the 119898th remark in

remark set VIn this paper the first-level fuzzy comprehensive evalua-

tion matrix 119861119894is calculated as follows

1198611= 1198821198711o1198771

= (020 007 037 008 022 006)

o

[[[[[[[

[

01277 04574 04149

04255 03830 05745

02660 05745 01595

00426 05638 03936

01702 03192 05106

00213 03617 06170

]]]]]]]

]

= (01690 04679 03631)

(8)

Similarly we can obtain

1198612= (01005 04585 04310)

1198613= (01073 05905 03022)

1198614= (01128 04736 04136)

1198615= (01710 05133 03157)

(9)

Then we obtain the second-level fuzzy relationmatrix1198771015840

1198771015840=

[[[[[

[

01690 04679 03631

01005 04585 04310

01073 05905 03022

01128 04736 04136

01710 05133 03157

]]]]]

]

(10)

The second-level fuzzy comprehensive evaluation matrixB can be calculated as follows

B = 119882o1198771015840

= (020 022 015 012 031)

o[[[[[

[

01690 04679 03631

01005 04585 04310

01073 05905 03022

01128 04736 04136

01710 05133 03157

]]]]]

]

= (01385 04990 03603)

(11)

47 Step 7 Rate and Conclude the Grade Level Accordingto the maximum membership degree principle when 119887

1198940=

max 119887119894(1 le 119894 le 119898) we can judge that the evaluated object

belongs to the 1198940grade

In this paper since 1198872

= max 119887119894(1 le 119894 le 3) =

04990 it is shown that the risk grade of ldquoZhejiang-FuzhourdquoUHV power transmission construction project belongs toldquomoderaterdquo which means the occurrence probability of thisproject risk is medium and the risk occurrence will causegeneral loss So it is necessary for the project managers to

Mathematical Problems in Engineering 11

Table 8 Judgment matrixes and weights of ldquosociety riskrdquo criteria

Society risk 11986234

11986235

11986236

11986237

11986238

11986239

Local weight11986234

1 23 12 18 2 3 02911986235

043 1 05 08 09 13 01211986236

083 2 1 15 17 25 02411986237

056 125 067 1 11 17 01611986238

05 011 059 091 1 15 01011986239

033 077 04 059 067 1 009120582max = 59109 CI = minus00178 CR = minus00141 lt 01

Table 9 The value of RI

119899 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15RI 0 052 089 112 126 136 141 145 149 152 154 156 157 158

carry out some specific risk control measures to make theconstruction of this project run successfully

At the meantime valuing the evaluation result of indi-cators in criteria layer in centesimal form can help projectmanagers to analyze the project riskmore efficiently Supposethe comment set V = [V

1 V2 V3] = 90 50 10 and then

the centesimal value of each indicator in criteria layer can becalculated as follows

1198801= 01690 times 90 + 04679 times 50 + 03631 times 10

= 422383

1198802= 01005 times 90 + 04585 times 50 + 04310 times 10

= 362830

1198803= 01073 times 90 + 05905 times 50 + 03022 times 10

= 422

1198804= 01128 times 90 + 04736 times 50 + 04136 times 10

= 379660

1198805= 01710 times 90 + 05133 times 50 + 03157 times 10

= 442085

(12)

The centesimal value (119880) of risk evaluation of ldquoZhejiang-Fuzhourdquo UHV power transmission construction project canbe calculated as

119880 = 01385 times 90 + 04990 times 50 + 03603 times 10

= 410205

(13)

Figure 8 compares the centesimal value of each indicatorin criteria layer and we can see

1198805≻ 1198801≻ 1198803≻ 119880 ≻ 119880

4≻ 1198802 (14)

Therefore the centesimal value of ldquosociety riskrdquo is thehighest followed by ldquopolicy and law riskrdquo ldquotechnology riskrdquoldquonatural environmental riskrdquo and ldquomanagement riskrdquo Thecentesimal values of both ldquomanagement riskrdquo and ldquonatural

422383

36283

422

37966

442085

Policy and law

Management

Technology

Natural environmental

Society

Centesimal value

Centesimal value of U

risk

risk

risk

risk

risk0 5 10 15 20 25 30 35 40 45 50

Figure 8 Centesimal value of each indicator in criteria layer

environmental riskrdquo are lower than that of the project119880 whilethe centesimal values of other three indicators are larger thanthat of the project 119880 The criteria ldquoSociety riskrdquo ldquopolicy andlaw riskrdquo and ldquotechnology riskrdquo should be paidmore attentionin the risk management and control for ldquoZhejiang-FuzhourdquoUHV power transmission construction project

5 Risk Control Recommendations

According to the risk evaluation result we should paymore attention to ldquosociety riskrdquo ldquopolicy and law riskrdquo andldquotechnology riskrdquoThe specific risk control recommendationsare as follows

51 Risk Control Recommendations for ldquoSociety Riskrdquo

(1) Before and during the construction of ldquoZhejiang-Fuzhourdquo UHV power transmission project the pro-paganda work should be done in the form of TVradio newspapers brochures and so on The con-struction significance and engineering safety knowl-edge related to this project should be propagandizedin order to eliminate the worries from society fol-lowers and local villagers about this UHV powertransmission project

12 Mathematical Problems in Engineering

Table 10 The weight of risk indicators

Criteria layer Index layerIndicator Weight (119882) Indicator Local weight (119882

119871) Global weight (119882

119866)

Policy and law risk (1198801) 020

1198621

020 004001198622

007 001401198623

037 007401198624

008 001601198625

022 004401198626

006 00120

Management risk (1198802) 022

1198627

003 000661198628

007 001541198629

009 0019811986210

006 0013211986211

004 0008811986212

011 0024211986213

009 0019811986214

006 0013211986215

012 0026411986216

009 0019811986217

003 0006611986218

005 0011011986219

004 0008811986220

004 0008811986221

004 0008811986222

003 00066

Technology risk (1198803) 015

11986223

014 0021011986224

020 0030011986225

007 0010511986226

006 0009011986227

011 0016511986228

009 0013511986229

013 0019511986230

014 0021011986231

006 00090

Natural environment risk (1198804) 012 119862

32064 00768

11986233

036 00432

Society risk (1198805) 031

11986234

029 0089911986235

012 0037211986236

024 0074411986237

016 0049611986238

01 0031011986239

009 00279

(2) Grid company should try to sign a contract withlocal government which strives to make the localgovernment be responsible for land requisition houserelocation and crop compensation Grid companycan also set up aworking group to coordinate with thelocal government The determination of land com-pensation standards not only abides by the relevantlaws and regulations but also takes the opinions oflocal masses into consideration

(3) The terrain and ecological resources along the projectline should be fully understood when selecting theoptimal route Having some experienced practition-ers on the team and considering the local customsare better for the route determination During theproject construction the water and soil loss as wellas deforestation should be reduced as far as possibleWhen the project is finished the vegetation should berestored timely

Mathematical Problems in Engineering 13

(4) Keep close touch with the local government andpublic security organization in order to strengthen thesecurity of project construction the ldquomass incidentsrdquosuch as petitions demagoguism and demonstrationshould be paid close attention and some relatedmeasures such as propaganda and negotiation shouldbe taken timely strengthen the project constructionmanagement and perform civilized construction andreduce the negative impacts on local residents to aminimum

52 Risk Control Recommendations for ldquoPolicy and Law Riskrdquo

(1) The project-related personnel especially the projectmanagers should carefully study the policies andlaws related to land management deforestation loanand environmental protection and the related legalcounsel should be engaged in order to reduce the legalrisk during the project construction

(2) Strengthen the research on the policies and guidancedocuments related to energy development and plan-ning

(3) Strengthen the communication with the governmentdepartment to improve the efficiency of project exam-ination and approval

(4) Because the size and weight of UHV equipment arebigger and heavier the traffic laws and regulationsshould be carefully studied to avoid the conflictrelated to UHV equipment transportation Trans-portation limitations should be taken into considera-tion when selecting the UHV equipment and surveyon the transport route is very necessary

53 Risk Control Recommendations for ldquoTechnology Riskrdquo

(1) Track the meteorological information timely andarrange the construction plan according to theweather condition some necessary measures shouldbe taken to protect the equipment from rainwatersuch as building the temporary drain and increasingthe pumping equipment

(2) The earth-rock excavation should keep a reasonableproportion based on the quantity calculation

(3) For waterway transport due to the constant changeof shipping lane the simulation navigation shouldbe performed six months in advance to ensure thetransportation safety

(4) Measure the earth resistivity and design the ground-ing grid establish special subjects to study the impactsof ground resistance on UHVGIS equipment and theoperation of control and protection system

(5) Design the crossing construction based on differ-ent crossing facilities to reduce the risk and diffi-culty when crossing the electricity lines the crossingscheme should be designed at the design stage and

take the terrain characteristic along the project lineinto consideration

(6) The material transport plan should take weather andtransportation environment into consideration opti-mize the use of different transportation facilities andmake the fullest use of crawler-transporter vehicleand cableway

6 Conclusions

In this paper a hybrid evaluation model based on AHPand FCE method is implemented to evaluate the risk ofldquoZhejiang-Fuzhourdquo UHV power transmission constructionprojectThis hybrid evaluationmodel takes full advantages ofAHP and FCEmethod After the risk evaluation index systemis built the AHP is used to determine the index weightand FCE method is used to evaluate the project risk Finallythe specific risk control recommendations are proposed Themain results of risk evaluation of ldquoZhejiang-Fuzhourdquo UHVpower transmission construction project are as follows

(1) The risk grade of ldquoZhejiang-Fuzhourdquo UHV powertransmission construction project belongs to ldquomod-eraterdquo which indicates the occurrence probability ofproject risk is medium and the risk occurrence willcause general loss

(2) ldquoSociety riskrdquo has the highest level and the next isldquopolicy and law riskrdquo ldquotechnique riskrdquo ldquonatural envi-ronmental riskrdquo and ldquomanagement riskrdquo respectivelyldquosociety riskrdquo ldquopolicy and law riskrdquo and ldquotechnologyriskrdquo should be paid more attention in the risk man-agement and control for ldquoZhejiang-Fuzhourdquo UHVpower transmission construction project

(3) Risk control recommendations for main risk criteriawhich include society risk policy and law risk andtechnology risk are proposed

(4) This hybrid evaluation model is feasible and effectivewhich can effectively evaluate the risk of UHV powertransmission construction project

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

This study is supported by the Humanity and Social Scienceproject of the Ministry of Education of China (Project no11YJA790217) and the National Natural Science Foundationof China (Project no 71373076)

References

[1] J P Liu D X Niu and X H Song ldquoThe energy supply anddemand pattern of China a review of evolution and sustainabledevelopmentrdquo Renewable and Sustainable Energy Reviews vol25 pp 220ndash228 2013

14 Mathematical Problems in Engineering

[2] C C Lin C H Yang and J Z Shyua ldquoA comparison ofinnovation policy in the smart grid industry across the pacificchina and the USArdquo Energy Policy vol 57 pp 119ndash132 2013

[3] M Bolinger and R Wiser ldquoA comparative analysis of businessstructures suitable for farmer-ownedwind power projects in theUnited Statesrdquo Energy Policy vol 34 no 14 pp 1750ndash1761 2006

[4] S Grassi N Chokani and R S Abhari ldquoLarge scale technicaland economical assessment of wind energy potential with a GIStool case study Iowardquo Energy Policy vol 45 pp 73ndash85 2012

[5] MHellstrom I Ruuska KWikstrom andD Jafs ldquoProject gov-ernance and path creation in the early stages of Finnish nuclearpower projectsrdquo International Journal of Project Managementvol 31 no 5 pp 712ndash723 2013

[6] P Baumann and G Stevanella ldquoFish passage principles to beconsidered for medium and large dams the case study of afish passage concept for a hydroelectric power project on theMekong mainstem in Laosrdquo Ecological Engineering vol 48 pp79ndash85 2012

[7] W Amatayakul and G Berndes ldquoDetermining factor for thedevelopment of CDM biomass power projectsrdquo Energy forSustainable Development vol 16 pp 197ndash203 2012

[8] J L Liu Q X Li and Y H Wang ldquoRisk analysis in ultradeep scientific drilling project-A fuzzy synthetic evaluationapproachrdquo International Journal of Project Management vol 31no 3 pp 449ndash458 2013

[9] A Badri S Nadeau and A Gbodossou ldquoA new practicalapproach to risk management for underground mining projectin Quebecrdquo Journal of Loss Prevention in the Process Industriesvol 26 no 6 pp 1145ndash1158 2013

[10] J B Song D R Song X Q Zhang and Y Sun ldquoRiskidentification for PPP waste-to-energy incineration projects inChinardquo Energy Policy vol 61 pp 953ndash962 2013

[11] Y Hu J F Du X Z Zhang et al ldquoAn integrative frameworkfor intelligent software project risk planningrdquo Decision SupportSystems vol 55 no 4 pp 927ndash937 2013

[12] T L Saaty The Analytic Hierarchy Process McGraw-Hill NewYork NY USA 1980

[13] M P Amiri ldquoProject selection for oil-fields development byusing the AHP and fuzzy TOPSIS methodsrdquo Expert Systemswith Applications vol 37 no 9 pp 6218ndash6224 2010

[14] H Z Li and S Guo ldquoExternal economies evaluation of windpower engineering project based on analytic hierarchy processand matter-element extension modelrdquo Mathematical Problemsin Engineering vol 2013 Article ID 848901 11 pages 2013

[15] F-G Chen H-L Yao andW-G Shi ldquoApplication of fuzzy andsynthetic judgment to risk assessment of dammed lakerdquo Journalof Shanghai Jiaotong University vol 45 no 1 pp 67ndash75 2011

[16] K Fang B-F He M Yang and Z-C Wang ldquoApplication offuzzy comprehensive evaluation method to CENSrdquo Journal ofHarbin Institute of Technology vol 43 no 5 pp 30ndash36 2011

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Mathematical Problems in Engineering

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Differential EquationsInternational Journal of

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Stochastic AnalysisInternational Journal of

6 Mathematical Problems in Engineering

Construct the hierarchical structure model

Construct the judgment matrixes

Determine the weight vector of risk index

Consistency test

Satisfied

Determine the evaluated object and evaluation index set

Give the remark set

Determine the index weight

Calculate the fuzzy relation matrix

Make fuzzy composition

Rate and conclude the grade level

AHP method to determine index weight

Nonsatisfied

Build the risk evaluation index system

Figure 4 The framework of risk evaluation

44 Step 4Determine the IndexWeight byUsingAHPMethodIn this paper the AHP method is employed to determinethe index weight After building the evaluation index systemthe local weight 119882

119871= 1199081198711

1199081198712

119908119871119899

and global weight119882119866

= 1199081198661

1199081198662

119908119866119899

of indicators in index layer andthe weight119882 = 119908

1 1199082 119908

ℎ of indicators in criteria layer

can be calculated where sum119899

119894=1119908119866119894

= 1 sumℎ119894=1

119908119894= 1 0 le 119908

119866119894

119908119894le 1

441 Substep 1 Construct the Hierarchical Structure ModelAccording to the overall goal and characteristics of MCDMproblem the complex determination of index weight isdecomposed and framed as a bottom-up hierarchical struc-ture which includes the goal layer criteria layer and indexlayer just as shown in Figure 5

In this paper the risk evaluation index system contains5 first-level risk criteria and 39 second-level risk indicatorsSuppose 119880 = 119880

1 1198802 1198803 1198804 1198805 = policy and law risk

management risk technology risk natural environment risksociety risks 119862 = 119862

1 1198622 119862

39 = project approval

policy risk adjustment risk on energy development strategyand electric planning policy land requisition and loggingpolicy risk social and public opinion risk The bottom-up hierarchical structure of risk evaluation of ldquoZhejiang-Fuzhourdquo UHV power transmission construction project isshown in Figure 6

Goal

Index

Criteria middot middot middot middot middot middot

middot middot middot middot middot middot middot middot middot

middot middot middot middot middot middot middot middot middot

Figure 5 The hierarchical structure of AHP for determining theindex weights

442 Substep 2 Construct the Judgment Matrixes The AHPuses the pairwise comparison method to construct thejudgmentmatrixes for both criteria layer and index layerThepairwise comparison is performed by using a nine-point scalewhich can convert human preference into quantitative valuejust as shown in Table 2

According to the analysis shown in Table 2 it shows that119886119894119895

gt 0 119886119894119894= 1 119886

119895119894= 1119886119894119895

In this paper after recognizing the judgments and opin-ions of experts and engineers related to UHV power trans-mission construction project according to the questionnaireresult the judgment matrixes of criteria layer and index layerby using the nine-point scale pair-wise comparison methodare constructed and the results are shown in Tables 3 4 5 67 and 8

Mathematical Problems in Engineering 7

Criteria

Risk evaluation of ldquoZhejiang-Fuzhourdquo UHV power transmission construction project

Policy and law risk Technology risk

Index

Management risk

Quality management risk

Security management risk

Goods and material management risk

Contract management risk

Bidding management risk

Project budget risk

Project design risk

Feasibility research risk

Other department coordination risk

Operation preparation risk

Completion inspection and approval risk

Debugging risk

Immature contractor risk

Supervision risk

Investment risk

Schedule risk

Project approval policy risk

Loan policy risk

Environmental protection law risk

Unsound traffic law risk

Adjustment risk on energy development strategy and electric

planning policy

Land requisition and logging policy risk

Substation construction risk

Technical immature risk

Depopulated zone construction risk

Mountain material transportation risk

Tower construction risk

Important line crossing risk

Equipment installation risk

Grounding projectresistance reduction risk

Large equipmenttransportation risk

Natural environment risk

Natural disaster

risk

Adverse geological condition

risk

Possible social risk due to immature

regime

Life security concern risk

Maladjustment risk to the living

environment changes

Possible ecological damage risk

Land requisition removing and crop compensation risk

Social and public opinion risk

Society risk

Goal

(C1)

(C2)

(C3)

(C4)

(C5)

(C6)

(C7)

(C8)

(C9)

(C10)

(C11)

(C12)

(C13)

(C14)

(C15)

(C16)

(C17)

(C18)

(C19)

(C20)

(C21)

(C22)

(C23)

(C24)

(C25)

(C26)

(C27)

(C28)

(C29)

(C30)

(C31)

(C32)

(C33)

(C34)

(C35)

(C36)

(C37)

(C38)

(C39)

(U1) (U2) (U3) (U4)(U5)

Figure 6 The hierarchical structure of risk evaluation

0

10

20

30

40

50

60

70

80

90

100

The o

btai

ned

frequ

ency

of e

ach

indi

cato

r

Risk indicator

C1

C3

C5

C7

C9

C11

C13

C15

C17

C19

C21

C23

C25

C27

C29

C31

C33

C35

C37

C39

High riskModerate riskLow risk

Figure 7 The obtained frequency of each indicator with differentrisk levels

Table 2 Nine-point comparison scale

Scale (119886119894119895) Meaning

1 Indicator 119909119894is of the same importance as indicator 119909

119895

3 Indicator 119909119894is slightly more important than indicator

119909119895

5 Indicator 119909119894is obviously more important than

indicator 119909119895

7 Indicator 119909119894is strongly more important than

indicator 119909119895

9 Indicator 119909119894is extremely more important than

indicator 119909119895

2 4 6 8 Middle value of aboveReciprocal 119909

119894119909119895= 119886119894119895 then 119909

119895119909119894= 119886119895119894

= 1119886119894119895

443 Substep 3 Determine the Weight Vector of Risk IndexAfter the judgment matrix is obtained the order weightvector of risk index can be calculated by using Eigenvalue

8 Mathematical Problems in Engineering

Table 3 Pairwise comparison judgment matrixes and weights in criteria layer

1198801

1198802

1198803

1198804

1198805

Weight1198801

100 090 140 180 065 0201198802

111 100 150 165 070 0221198803

071 067 100 125 045 0151198804

056 061 080 100 040 0121198805

154 143 222 250 100 031120582max = 50034 CI = 000084 CR = 000075 lt 01

Table 4 Judgment matrixes and weights of ldquopolicy and law riskrdquo criteria

Policy and law risk 1198621

1198622

1198623

1198624

1198625

1198626

Local weight1198621

100 300 050 250 080 350 0201198622

033 100 020 090 033 120 0071198623

200 500 100 450 200 520 0371198624

040 111 022 100 030 160 0081198625

125 300 050 333 100 320 0221198626

029 083 019 063 031 100 006120582max = 60297 CI = 00059 CR = 00048 lt 01

Table 5 Judgment matrixes and weights of ldquomanagement riskrdquo criteria

Managementrisk 119862

71198628

1198629

11986210

11986211

11986212

11986213

11986214

11986215

11986216

11986217

11986218

11986219

11986220

11986221

11986222 Local weight

1198627

100 033 029 050 067 025 028 050 024 028 091 056 077 083 083 091 003

1198628

300 100 091 120 150 067 071 130 040 067 250 180 200 220 230 250 007

1198629

350 110 100 150 250 083 100 150 083 100 250 200 260 280 280 300 009

11986210

200 083 067 100 120 050 056 100 045 067 150 120 150 160 160 180 006

11986211

150 067 040 083 100 033 045 077 029 040 130 083 110 120 120 130 004

11986212

400 150 120 200 300 100 120 180 083 120 320 200 280 300 300 320 011

11986213

360 140 100 180 220 083 100 160 083 100 280 180 220 230 230 250 009

11986214

200 077 067 100 130 056 063 100 050 056 180 110 150 160 160 180 006

11986215

420 250 120 220 350 120 120 200 100 120 400 220 300 320 320 350 012

11986216

360 150 100 150 250 083 100 180 083 100 250 180 220 240 240 250 009

11986217

110 040 040 067 077 031 036 056 025 040 100 067 083 091 091 100 003

11986218

180 056 050 083 120 050 056 091 045 056 150 100 150 160 160 180 005

11986219

130 050 038 067 091 036 045 067 033 045 120 067 100 120 120 110 004

11986220

120 045 036 063 083 033 043 063 031 042 110 063 083 100 100 110 004

11986221

120 043 036 063 083 033 043 063 031 042 110 063 083 100 100 110 004

11986222

110 04 033 056 077 031 040 056 029 040 100 056 091 091 091 100 003120582max = 16055 CI = 0003697 CR = 00023 lt 01

method The eigenvector of judgment matrix with the max-imum eigenvalue is the weight vector of risk index whichdenotes the relative importance of indicators in the same levelwith regard to the indicators in the upper layer The weightvector of risk index is the relative importance of indicators

with regard to the upper layer indicator which is also calledthe local weight

In this paper the weights of indictors in criteria layer andlocal weights of indicators in index layer are calculated whichare lists in Tables 3ndash8 respectively

Mathematical Problems in Engineering 9

Table 6 Judgment matrixes and weights of ldquotechnology riskrdquo criteria

Technology risk 11986223

11986224

11986225

11986226

11986227

11986228

11986229

11986230

11986231

Local weight11986223

100 067 222 222 125 167 111 100 250 01411986224

150 100 286 333 167 250 143 133 333 02011986225

045 035 100 111 059 080 056 050 125 00711986226

045 030 090 100 056 071 050 045 111 00611986227

080 060 170 180 100 133 083 080 200 01111986228

060 040 125 140 075 100 067 067 143 00911986229

090 070 180 200 120 150 100 091 222 01311986230

100 075 200 220 125 150 110 100 250 01411986231

040 030 080 090 050 070 045 040 100 006120582max = 900585 CI = 0000731 CR = 0000504 lt 01

Table 7 Judgment matrixes and weights of ldquonatural environmentriskrdquo criteria

Natural environment risk 11986232

11986233

Local weight11986232

1 18 06411986233

056 1 036120582max = 2 CI = 0 CR = 0 lt 01

444 Substep 4 Consistency Test The consistency of relativeimportance judgment on each indicator made by expertsand engineers is the key prerequisite for using the AHP todetermine the weights of risk indicators Hence it is verynecessary to test the consistency of judgment matrix Whenthe consistency of judgmentmatrix is satisfied themaximumeigenvalue of the judgmentmatrix120582max should be equal to thenumber of indicators which are related to two consistencytest indices namely CI and CR

Consistency index (CI) which measures the divergenceof judgment matrix away from the consistency is defined asfollows

CI =120582max minus 119899

119899 minus 1 (1)

where 119899 represents the number of indicesThus the consistency ratio (CR) is defined as follows

CR =CIRI

(2)

RI is the random consistency index which is the averagevalue of eigenvalues obtained by calculating the judgmentmatrix for more than 500 times The value of RI is given inTable 9

If CR lt 01 the weight vector is acceptable otherwisethe modification of the pairwise judgment matrix is needed

As listed in the last row in Tables 3ndash8 respectivelyall the pairwise comparison judgment matrixes satisfy theconsistency test

445 Substep 5 Calculate the Index Weight The globalweight of each indicator can be determined by multiplying

the local weight of the indicator with theweight of upper layerindicator which locates in the parent node above it

The local and global weights of each risk indicator inindex layer and the weight of each indicator in criteria layerare calculated which are listed in Table 10

45 Step 5 Calculate the Fuzzy Relation Matrix Accordingto the statistical result of the questionnaire by using a certainmathematical method such as frequency-based method andweighted averagemethod the first-level fuzzy relationmatrixR can be calculated as follows

R = (119903119894119895)119899times119898

=

[[[[

[

11990311

11990312

1199031119898

11990321

11990322

1199032119898

1199031198991

1199031198992

119903119899119898

]]]]

]

(3)

where 119903119894119895is the membership degree of the 119895th remark in

remark set V for the indicator 119894 119894 = 1 2 119899 119895 =

1 2 119898 119899 is the number of indices and 119898 is the numberof risk grades in remark set V Different rows in the fuzzyrelation matrix R reflect the different membership degrees ofevaluated object subject to fuzzy set of each grade consideringdifferent evaluation indices

The frequency-based method is used to establish thefuzzy relation matrix in this paper the principle of which isif the number of experts and engineers who judge the ldquohighriskrdquo ldquomoderate riskrdquo and ldquolow riskrdquo is119898

1 1198982 and119898

3respec-

tively then the set (1198981sum3

119896=1119898119896 1198982sum3

119896=1119898119896 1198983sum3

119896=1119898119896)

is the membership set of the evaluation index The obtainedfrequency of each indicator with different risk grades is listedin Figure 7

Thus the first-level fuzzy relation matrix R can becalculated just as follows

1198771=

[[[[[[[

[

01277 04574 04149

04255 03830 05745

02660 05745 01595

00426 05638 03936

01702 03192 05106

00213 03617 06170

]]]]]]]

]

10 Mathematical Problems in Engineering

1198772=

[[[[[[[[[[[[[[[[[[[[[[[[[[

[

00106 04362 05532

00957 04894 04149

01170 05532 03298

00957 03298 05745

00638 04681 04681

01489 03617 04894

01383 04894 03723

00745 04787 04468

01596 03723 04681

01170 06915 01915

00426 04574 05000

00851 03830 05319

00532 04681 04787

00426 04149 05425

00426 04574 05000

00213 05638 04149

]]]]]]]]]]]]]]]]]]]]]]]]]]

]

1198773=

[[[[[[[[[[[[

[

01170 04787 04043

02021 04149 03830

00638 04575 04787

00532 04255 05213

00851 07447 01702

00638 07766 01596

00851 08404 00745

00958 07340 01702

00532 03191 06277

]]]]]]]]]]]]

]

1198774= [

01702 04468 03830

00106 05213 04681]

1198775=

[[[[[[[

[

02447 05638 01915

00957 05000 04043

02340 04787 02872

01064 04894 04042

00957 04681 04362

00638 05532 03830

]]]]]]]

]

(4)

46 Step 6 Make Fuzzy Composition Synthesize the first-level fuzzy relation matrix R with the local weight 119882

119871 and

then the membership matrix 119861119894could be obtained which is

call the first-level fuzzy comprehensive evaluation matrix

119861119894= 119882119871o119877 = (119887

1198941 1198871198942 119887

119894119898) (5)

Due to the hierarchical structure of the evaluation indexsystem the second-level fuzzy relation matrix 119877

1015840 needs to becalculated

1198771015840=

[[[[

[

1198611

1198612

119861119896

]]]]

]

=[[[

[

11988711

11988712

sdot sdot sdot 1198871119898

11988721

11988722

sdot sdot sdot 1198872119898

sdot sdot sdot sdot sdot sdot sdot sdot sdot sdot sdot sdot

1198871198961

1198871198962

sdot sdot sdot 119887119896119898

]]]

]

(6)

Then combined with the weight matrix 119882 the second-level fuzzy comprehensive evaluation matrix B can be calcu-lated as follows

B = 119882o1198771015840 = (1198871 1198872 119887

119898) (7)

where 119887119898is the membership degree of the 119898th remark in

remark set VIn this paper the first-level fuzzy comprehensive evalua-

tion matrix 119861119894is calculated as follows

1198611= 1198821198711o1198771

= (020 007 037 008 022 006)

o

[[[[[[[

[

01277 04574 04149

04255 03830 05745

02660 05745 01595

00426 05638 03936

01702 03192 05106

00213 03617 06170

]]]]]]]

]

= (01690 04679 03631)

(8)

Similarly we can obtain

1198612= (01005 04585 04310)

1198613= (01073 05905 03022)

1198614= (01128 04736 04136)

1198615= (01710 05133 03157)

(9)

Then we obtain the second-level fuzzy relationmatrix1198771015840

1198771015840=

[[[[[

[

01690 04679 03631

01005 04585 04310

01073 05905 03022

01128 04736 04136

01710 05133 03157

]]]]]

]

(10)

The second-level fuzzy comprehensive evaluation matrixB can be calculated as follows

B = 119882o1198771015840

= (020 022 015 012 031)

o[[[[[

[

01690 04679 03631

01005 04585 04310

01073 05905 03022

01128 04736 04136

01710 05133 03157

]]]]]

]

= (01385 04990 03603)

(11)

47 Step 7 Rate and Conclude the Grade Level Accordingto the maximum membership degree principle when 119887

1198940=

max 119887119894(1 le 119894 le 119898) we can judge that the evaluated object

belongs to the 1198940grade

In this paper since 1198872

= max 119887119894(1 le 119894 le 3) =

04990 it is shown that the risk grade of ldquoZhejiang-FuzhourdquoUHV power transmission construction project belongs toldquomoderaterdquo which means the occurrence probability of thisproject risk is medium and the risk occurrence will causegeneral loss So it is necessary for the project managers to

Mathematical Problems in Engineering 11

Table 8 Judgment matrixes and weights of ldquosociety riskrdquo criteria

Society risk 11986234

11986235

11986236

11986237

11986238

11986239

Local weight11986234

1 23 12 18 2 3 02911986235

043 1 05 08 09 13 01211986236

083 2 1 15 17 25 02411986237

056 125 067 1 11 17 01611986238

05 011 059 091 1 15 01011986239

033 077 04 059 067 1 009120582max = 59109 CI = minus00178 CR = minus00141 lt 01

Table 9 The value of RI

119899 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15RI 0 052 089 112 126 136 141 145 149 152 154 156 157 158

carry out some specific risk control measures to make theconstruction of this project run successfully

At the meantime valuing the evaluation result of indi-cators in criteria layer in centesimal form can help projectmanagers to analyze the project riskmore efficiently Supposethe comment set V = [V

1 V2 V3] = 90 50 10 and then

the centesimal value of each indicator in criteria layer can becalculated as follows

1198801= 01690 times 90 + 04679 times 50 + 03631 times 10

= 422383

1198802= 01005 times 90 + 04585 times 50 + 04310 times 10

= 362830

1198803= 01073 times 90 + 05905 times 50 + 03022 times 10

= 422

1198804= 01128 times 90 + 04736 times 50 + 04136 times 10

= 379660

1198805= 01710 times 90 + 05133 times 50 + 03157 times 10

= 442085

(12)

The centesimal value (119880) of risk evaluation of ldquoZhejiang-Fuzhourdquo UHV power transmission construction project canbe calculated as

119880 = 01385 times 90 + 04990 times 50 + 03603 times 10

= 410205

(13)

Figure 8 compares the centesimal value of each indicatorin criteria layer and we can see

1198805≻ 1198801≻ 1198803≻ 119880 ≻ 119880

4≻ 1198802 (14)

Therefore the centesimal value of ldquosociety riskrdquo is thehighest followed by ldquopolicy and law riskrdquo ldquotechnology riskrdquoldquonatural environmental riskrdquo and ldquomanagement riskrdquo Thecentesimal values of both ldquomanagement riskrdquo and ldquonatural

422383

36283

422

37966

442085

Policy and law

Management

Technology

Natural environmental

Society

Centesimal value

Centesimal value of U

risk

risk

risk

risk

risk0 5 10 15 20 25 30 35 40 45 50

Figure 8 Centesimal value of each indicator in criteria layer

environmental riskrdquo are lower than that of the project119880 whilethe centesimal values of other three indicators are larger thanthat of the project 119880 The criteria ldquoSociety riskrdquo ldquopolicy andlaw riskrdquo and ldquotechnology riskrdquo should be paidmore attentionin the risk management and control for ldquoZhejiang-FuzhourdquoUHV power transmission construction project

5 Risk Control Recommendations

According to the risk evaluation result we should paymore attention to ldquosociety riskrdquo ldquopolicy and law riskrdquo andldquotechnology riskrdquoThe specific risk control recommendationsare as follows

51 Risk Control Recommendations for ldquoSociety Riskrdquo

(1) Before and during the construction of ldquoZhejiang-Fuzhourdquo UHV power transmission project the pro-paganda work should be done in the form of TVradio newspapers brochures and so on The con-struction significance and engineering safety knowl-edge related to this project should be propagandizedin order to eliminate the worries from society fol-lowers and local villagers about this UHV powertransmission project

12 Mathematical Problems in Engineering

Table 10 The weight of risk indicators

Criteria layer Index layerIndicator Weight (119882) Indicator Local weight (119882

119871) Global weight (119882

119866)

Policy and law risk (1198801) 020

1198621

020 004001198622

007 001401198623

037 007401198624

008 001601198625

022 004401198626

006 00120

Management risk (1198802) 022

1198627

003 000661198628

007 001541198629

009 0019811986210

006 0013211986211

004 0008811986212

011 0024211986213

009 0019811986214

006 0013211986215

012 0026411986216

009 0019811986217

003 0006611986218

005 0011011986219

004 0008811986220

004 0008811986221

004 0008811986222

003 00066

Technology risk (1198803) 015

11986223

014 0021011986224

020 0030011986225

007 0010511986226

006 0009011986227

011 0016511986228

009 0013511986229

013 0019511986230

014 0021011986231

006 00090

Natural environment risk (1198804) 012 119862

32064 00768

11986233

036 00432

Society risk (1198805) 031

11986234

029 0089911986235

012 0037211986236

024 0074411986237

016 0049611986238

01 0031011986239

009 00279

(2) Grid company should try to sign a contract withlocal government which strives to make the localgovernment be responsible for land requisition houserelocation and crop compensation Grid companycan also set up aworking group to coordinate with thelocal government The determination of land com-pensation standards not only abides by the relevantlaws and regulations but also takes the opinions oflocal masses into consideration

(3) The terrain and ecological resources along the projectline should be fully understood when selecting theoptimal route Having some experienced practition-ers on the team and considering the local customsare better for the route determination During theproject construction the water and soil loss as wellas deforestation should be reduced as far as possibleWhen the project is finished the vegetation should berestored timely

Mathematical Problems in Engineering 13

(4) Keep close touch with the local government andpublic security organization in order to strengthen thesecurity of project construction the ldquomass incidentsrdquosuch as petitions demagoguism and demonstrationshould be paid close attention and some relatedmeasures such as propaganda and negotiation shouldbe taken timely strengthen the project constructionmanagement and perform civilized construction andreduce the negative impacts on local residents to aminimum

52 Risk Control Recommendations for ldquoPolicy and Law Riskrdquo

(1) The project-related personnel especially the projectmanagers should carefully study the policies andlaws related to land management deforestation loanand environmental protection and the related legalcounsel should be engaged in order to reduce the legalrisk during the project construction

(2) Strengthen the research on the policies and guidancedocuments related to energy development and plan-ning

(3) Strengthen the communication with the governmentdepartment to improve the efficiency of project exam-ination and approval

(4) Because the size and weight of UHV equipment arebigger and heavier the traffic laws and regulationsshould be carefully studied to avoid the conflictrelated to UHV equipment transportation Trans-portation limitations should be taken into considera-tion when selecting the UHV equipment and surveyon the transport route is very necessary

53 Risk Control Recommendations for ldquoTechnology Riskrdquo

(1) Track the meteorological information timely andarrange the construction plan according to theweather condition some necessary measures shouldbe taken to protect the equipment from rainwatersuch as building the temporary drain and increasingthe pumping equipment

(2) The earth-rock excavation should keep a reasonableproportion based on the quantity calculation

(3) For waterway transport due to the constant changeof shipping lane the simulation navigation shouldbe performed six months in advance to ensure thetransportation safety

(4) Measure the earth resistivity and design the ground-ing grid establish special subjects to study the impactsof ground resistance on UHVGIS equipment and theoperation of control and protection system

(5) Design the crossing construction based on differ-ent crossing facilities to reduce the risk and diffi-culty when crossing the electricity lines the crossingscheme should be designed at the design stage and

take the terrain characteristic along the project lineinto consideration

(6) The material transport plan should take weather andtransportation environment into consideration opti-mize the use of different transportation facilities andmake the fullest use of crawler-transporter vehicleand cableway

6 Conclusions

In this paper a hybrid evaluation model based on AHPand FCE method is implemented to evaluate the risk ofldquoZhejiang-Fuzhourdquo UHV power transmission constructionprojectThis hybrid evaluationmodel takes full advantages ofAHP and FCEmethod After the risk evaluation index systemis built the AHP is used to determine the index weightand FCE method is used to evaluate the project risk Finallythe specific risk control recommendations are proposed Themain results of risk evaluation of ldquoZhejiang-Fuzhourdquo UHVpower transmission construction project are as follows

(1) The risk grade of ldquoZhejiang-Fuzhourdquo UHV powertransmission construction project belongs to ldquomod-eraterdquo which indicates the occurrence probability ofproject risk is medium and the risk occurrence willcause general loss

(2) ldquoSociety riskrdquo has the highest level and the next isldquopolicy and law riskrdquo ldquotechnique riskrdquo ldquonatural envi-ronmental riskrdquo and ldquomanagement riskrdquo respectivelyldquosociety riskrdquo ldquopolicy and law riskrdquo and ldquotechnologyriskrdquo should be paid more attention in the risk man-agement and control for ldquoZhejiang-Fuzhourdquo UHVpower transmission construction project

(3) Risk control recommendations for main risk criteriawhich include society risk policy and law risk andtechnology risk are proposed

(4) This hybrid evaluation model is feasible and effectivewhich can effectively evaluate the risk of UHV powertransmission construction project

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

This study is supported by the Humanity and Social Scienceproject of the Ministry of Education of China (Project no11YJA790217) and the National Natural Science Foundationof China (Project no 71373076)

References

[1] J P Liu D X Niu and X H Song ldquoThe energy supply anddemand pattern of China a review of evolution and sustainabledevelopmentrdquo Renewable and Sustainable Energy Reviews vol25 pp 220ndash228 2013

14 Mathematical Problems in Engineering

[2] C C Lin C H Yang and J Z Shyua ldquoA comparison ofinnovation policy in the smart grid industry across the pacificchina and the USArdquo Energy Policy vol 57 pp 119ndash132 2013

[3] M Bolinger and R Wiser ldquoA comparative analysis of businessstructures suitable for farmer-ownedwind power projects in theUnited Statesrdquo Energy Policy vol 34 no 14 pp 1750ndash1761 2006

[4] S Grassi N Chokani and R S Abhari ldquoLarge scale technicaland economical assessment of wind energy potential with a GIStool case study Iowardquo Energy Policy vol 45 pp 73ndash85 2012

[5] MHellstrom I Ruuska KWikstrom andD Jafs ldquoProject gov-ernance and path creation in the early stages of Finnish nuclearpower projectsrdquo International Journal of Project Managementvol 31 no 5 pp 712ndash723 2013

[6] P Baumann and G Stevanella ldquoFish passage principles to beconsidered for medium and large dams the case study of afish passage concept for a hydroelectric power project on theMekong mainstem in Laosrdquo Ecological Engineering vol 48 pp79ndash85 2012

[7] W Amatayakul and G Berndes ldquoDetermining factor for thedevelopment of CDM biomass power projectsrdquo Energy forSustainable Development vol 16 pp 197ndash203 2012

[8] J L Liu Q X Li and Y H Wang ldquoRisk analysis in ultradeep scientific drilling project-A fuzzy synthetic evaluationapproachrdquo International Journal of Project Management vol 31no 3 pp 449ndash458 2013

[9] A Badri S Nadeau and A Gbodossou ldquoA new practicalapproach to risk management for underground mining projectin Quebecrdquo Journal of Loss Prevention in the Process Industriesvol 26 no 6 pp 1145ndash1158 2013

[10] J B Song D R Song X Q Zhang and Y Sun ldquoRiskidentification for PPP waste-to-energy incineration projects inChinardquo Energy Policy vol 61 pp 953ndash962 2013

[11] Y Hu J F Du X Z Zhang et al ldquoAn integrative frameworkfor intelligent software project risk planningrdquo Decision SupportSystems vol 55 no 4 pp 927ndash937 2013

[12] T L Saaty The Analytic Hierarchy Process McGraw-Hill NewYork NY USA 1980

[13] M P Amiri ldquoProject selection for oil-fields development byusing the AHP and fuzzy TOPSIS methodsrdquo Expert Systemswith Applications vol 37 no 9 pp 6218ndash6224 2010

[14] H Z Li and S Guo ldquoExternal economies evaluation of windpower engineering project based on analytic hierarchy processand matter-element extension modelrdquo Mathematical Problemsin Engineering vol 2013 Article ID 848901 11 pages 2013

[15] F-G Chen H-L Yao andW-G Shi ldquoApplication of fuzzy andsynthetic judgment to risk assessment of dammed lakerdquo Journalof Shanghai Jiaotong University vol 45 no 1 pp 67ndash75 2011

[16] K Fang B-F He M Yang and Z-C Wang ldquoApplication offuzzy comprehensive evaluation method to CENSrdquo Journal ofHarbin Institute of Technology vol 43 no 5 pp 30ndash36 2011

Submit your manuscripts athttpwwwhindawicom

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mathematical Problems in Engineering

Hindawi Publishing Corporationhttpwwwhindawicom

Differential EquationsInternational Journal of

Volume 2014

Applied MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mathematical PhysicsAdvances in

Complex AnalysisJournal of

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OptimizationJournal of

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CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Operations ResearchAdvances in

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Function Spaces

Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of Mathematics and Mathematical Sciences

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

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Algebra

Discrete Dynamics in Nature and Society

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Decision SciencesAdvances in

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Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Stochastic AnalysisInternational Journal of

Mathematical Problems in Engineering 7

Criteria

Risk evaluation of ldquoZhejiang-Fuzhourdquo UHV power transmission construction project

Policy and law risk Technology risk

Index

Management risk

Quality management risk

Security management risk

Goods and material management risk

Contract management risk

Bidding management risk

Project budget risk

Project design risk

Feasibility research risk

Other department coordination risk

Operation preparation risk

Completion inspection and approval risk

Debugging risk

Immature contractor risk

Supervision risk

Investment risk

Schedule risk

Project approval policy risk

Loan policy risk

Environmental protection law risk

Unsound traffic law risk

Adjustment risk on energy development strategy and electric

planning policy

Land requisition and logging policy risk

Substation construction risk

Technical immature risk

Depopulated zone construction risk

Mountain material transportation risk

Tower construction risk

Important line crossing risk

Equipment installation risk

Grounding projectresistance reduction risk

Large equipmenttransportation risk

Natural environment risk

Natural disaster

risk

Adverse geological condition

risk

Possible social risk due to immature

regime

Life security concern risk

Maladjustment risk to the living

environment changes

Possible ecological damage risk

Land requisition removing and crop compensation risk

Social and public opinion risk

Society risk

Goal

(C1)

(C2)

(C3)

(C4)

(C5)

(C6)

(C7)

(C8)

(C9)

(C10)

(C11)

(C12)

(C13)

(C14)

(C15)

(C16)

(C17)

(C18)

(C19)

(C20)

(C21)

(C22)

(C23)

(C24)

(C25)

(C26)

(C27)

(C28)

(C29)

(C30)

(C31)

(C32)

(C33)

(C34)

(C35)

(C36)

(C37)

(C38)

(C39)

(U1) (U2) (U3) (U4)(U5)

Figure 6 The hierarchical structure of risk evaluation

0

10

20

30

40

50

60

70

80

90

100

The o

btai

ned

frequ

ency

of e

ach

indi

cato

r

Risk indicator

C1

C3

C5

C7

C9

C11

C13

C15

C17

C19

C21

C23

C25

C27

C29

C31

C33

C35

C37

C39

High riskModerate riskLow risk

Figure 7 The obtained frequency of each indicator with differentrisk levels

Table 2 Nine-point comparison scale

Scale (119886119894119895) Meaning

1 Indicator 119909119894is of the same importance as indicator 119909

119895

3 Indicator 119909119894is slightly more important than indicator

119909119895

5 Indicator 119909119894is obviously more important than

indicator 119909119895

7 Indicator 119909119894is strongly more important than

indicator 119909119895

9 Indicator 119909119894is extremely more important than

indicator 119909119895

2 4 6 8 Middle value of aboveReciprocal 119909

119894119909119895= 119886119894119895 then 119909

119895119909119894= 119886119895119894

= 1119886119894119895

443 Substep 3 Determine the Weight Vector of Risk IndexAfter the judgment matrix is obtained the order weightvector of risk index can be calculated by using Eigenvalue

8 Mathematical Problems in Engineering

Table 3 Pairwise comparison judgment matrixes and weights in criteria layer

1198801

1198802

1198803

1198804

1198805

Weight1198801

100 090 140 180 065 0201198802

111 100 150 165 070 0221198803

071 067 100 125 045 0151198804

056 061 080 100 040 0121198805

154 143 222 250 100 031120582max = 50034 CI = 000084 CR = 000075 lt 01

Table 4 Judgment matrixes and weights of ldquopolicy and law riskrdquo criteria

Policy and law risk 1198621

1198622

1198623

1198624

1198625

1198626

Local weight1198621

100 300 050 250 080 350 0201198622

033 100 020 090 033 120 0071198623

200 500 100 450 200 520 0371198624

040 111 022 100 030 160 0081198625

125 300 050 333 100 320 0221198626

029 083 019 063 031 100 006120582max = 60297 CI = 00059 CR = 00048 lt 01

Table 5 Judgment matrixes and weights of ldquomanagement riskrdquo criteria

Managementrisk 119862

71198628

1198629

11986210

11986211

11986212

11986213

11986214

11986215

11986216

11986217

11986218

11986219

11986220

11986221

11986222 Local weight

1198627

100 033 029 050 067 025 028 050 024 028 091 056 077 083 083 091 003

1198628

300 100 091 120 150 067 071 130 040 067 250 180 200 220 230 250 007

1198629

350 110 100 150 250 083 100 150 083 100 250 200 260 280 280 300 009

11986210

200 083 067 100 120 050 056 100 045 067 150 120 150 160 160 180 006

11986211

150 067 040 083 100 033 045 077 029 040 130 083 110 120 120 130 004

11986212

400 150 120 200 300 100 120 180 083 120 320 200 280 300 300 320 011

11986213

360 140 100 180 220 083 100 160 083 100 280 180 220 230 230 250 009

11986214

200 077 067 100 130 056 063 100 050 056 180 110 150 160 160 180 006

11986215

420 250 120 220 350 120 120 200 100 120 400 220 300 320 320 350 012

11986216

360 150 100 150 250 083 100 180 083 100 250 180 220 240 240 250 009

11986217

110 040 040 067 077 031 036 056 025 040 100 067 083 091 091 100 003

11986218

180 056 050 083 120 050 056 091 045 056 150 100 150 160 160 180 005

11986219

130 050 038 067 091 036 045 067 033 045 120 067 100 120 120 110 004

11986220

120 045 036 063 083 033 043 063 031 042 110 063 083 100 100 110 004

11986221

120 043 036 063 083 033 043 063 031 042 110 063 083 100 100 110 004

11986222

110 04 033 056 077 031 040 056 029 040 100 056 091 091 091 100 003120582max = 16055 CI = 0003697 CR = 00023 lt 01

method The eigenvector of judgment matrix with the max-imum eigenvalue is the weight vector of risk index whichdenotes the relative importance of indicators in the same levelwith regard to the indicators in the upper layer The weightvector of risk index is the relative importance of indicators

with regard to the upper layer indicator which is also calledthe local weight

In this paper the weights of indictors in criteria layer andlocal weights of indicators in index layer are calculated whichare lists in Tables 3ndash8 respectively

Mathematical Problems in Engineering 9

Table 6 Judgment matrixes and weights of ldquotechnology riskrdquo criteria

Technology risk 11986223

11986224

11986225

11986226

11986227

11986228

11986229

11986230

11986231

Local weight11986223

100 067 222 222 125 167 111 100 250 01411986224

150 100 286 333 167 250 143 133 333 02011986225

045 035 100 111 059 080 056 050 125 00711986226

045 030 090 100 056 071 050 045 111 00611986227

080 060 170 180 100 133 083 080 200 01111986228

060 040 125 140 075 100 067 067 143 00911986229

090 070 180 200 120 150 100 091 222 01311986230

100 075 200 220 125 150 110 100 250 01411986231

040 030 080 090 050 070 045 040 100 006120582max = 900585 CI = 0000731 CR = 0000504 lt 01

Table 7 Judgment matrixes and weights of ldquonatural environmentriskrdquo criteria

Natural environment risk 11986232

11986233

Local weight11986232

1 18 06411986233

056 1 036120582max = 2 CI = 0 CR = 0 lt 01

444 Substep 4 Consistency Test The consistency of relativeimportance judgment on each indicator made by expertsand engineers is the key prerequisite for using the AHP todetermine the weights of risk indicators Hence it is verynecessary to test the consistency of judgment matrix Whenthe consistency of judgmentmatrix is satisfied themaximumeigenvalue of the judgmentmatrix120582max should be equal to thenumber of indicators which are related to two consistencytest indices namely CI and CR

Consistency index (CI) which measures the divergenceof judgment matrix away from the consistency is defined asfollows

CI =120582max minus 119899

119899 minus 1 (1)

where 119899 represents the number of indicesThus the consistency ratio (CR) is defined as follows

CR =CIRI

(2)

RI is the random consistency index which is the averagevalue of eigenvalues obtained by calculating the judgmentmatrix for more than 500 times The value of RI is given inTable 9

If CR lt 01 the weight vector is acceptable otherwisethe modification of the pairwise judgment matrix is needed

As listed in the last row in Tables 3ndash8 respectivelyall the pairwise comparison judgment matrixes satisfy theconsistency test

445 Substep 5 Calculate the Index Weight The globalweight of each indicator can be determined by multiplying

the local weight of the indicator with theweight of upper layerindicator which locates in the parent node above it

The local and global weights of each risk indicator inindex layer and the weight of each indicator in criteria layerare calculated which are listed in Table 10

45 Step 5 Calculate the Fuzzy Relation Matrix Accordingto the statistical result of the questionnaire by using a certainmathematical method such as frequency-based method andweighted averagemethod the first-level fuzzy relationmatrixR can be calculated as follows

R = (119903119894119895)119899times119898

=

[[[[

[

11990311

11990312

1199031119898

11990321

11990322

1199032119898

1199031198991

1199031198992

119903119899119898

]]]]

]

(3)

where 119903119894119895is the membership degree of the 119895th remark in

remark set V for the indicator 119894 119894 = 1 2 119899 119895 =

1 2 119898 119899 is the number of indices and 119898 is the numberof risk grades in remark set V Different rows in the fuzzyrelation matrix R reflect the different membership degrees ofevaluated object subject to fuzzy set of each grade consideringdifferent evaluation indices

The frequency-based method is used to establish thefuzzy relation matrix in this paper the principle of which isif the number of experts and engineers who judge the ldquohighriskrdquo ldquomoderate riskrdquo and ldquolow riskrdquo is119898

1 1198982 and119898

3respec-

tively then the set (1198981sum3

119896=1119898119896 1198982sum3

119896=1119898119896 1198983sum3

119896=1119898119896)

is the membership set of the evaluation index The obtainedfrequency of each indicator with different risk grades is listedin Figure 7

Thus the first-level fuzzy relation matrix R can becalculated just as follows

1198771=

[[[[[[[

[

01277 04574 04149

04255 03830 05745

02660 05745 01595

00426 05638 03936

01702 03192 05106

00213 03617 06170

]]]]]]]

]

10 Mathematical Problems in Engineering

1198772=

[[[[[[[[[[[[[[[[[[[[[[[[[[

[

00106 04362 05532

00957 04894 04149

01170 05532 03298

00957 03298 05745

00638 04681 04681

01489 03617 04894

01383 04894 03723

00745 04787 04468

01596 03723 04681

01170 06915 01915

00426 04574 05000

00851 03830 05319

00532 04681 04787

00426 04149 05425

00426 04574 05000

00213 05638 04149

]]]]]]]]]]]]]]]]]]]]]]]]]]

]

1198773=

[[[[[[[[[[[[

[

01170 04787 04043

02021 04149 03830

00638 04575 04787

00532 04255 05213

00851 07447 01702

00638 07766 01596

00851 08404 00745

00958 07340 01702

00532 03191 06277

]]]]]]]]]]]]

]

1198774= [

01702 04468 03830

00106 05213 04681]

1198775=

[[[[[[[

[

02447 05638 01915

00957 05000 04043

02340 04787 02872

01064 04894 04042

00957 04681 04362

00638 05532 03830

]]]]]]]

]

(4)

46 Step 6 Make Fuzzy Composition Synthesize the first-level fuzzy relation matrix R with the local weight 119882

119871 and

then the membership matrix 119861119894could be obtained which is

call the first-level fuzzy comprehensive evaluation matrix

119861119894= 119882119871o119877 = (119887

1198941 1198871198942 119887

119894119898) (5)

Due to the hierarchical structure of the evaluation indexsystem the second-level fuzzy relation matrix 119877

1015840 needs to becalculated

1198771015840=

[[[[

[

1198611

1198612

119861119896

]]]]

]

=[[[

[

11988711

11988712

sdot sdot sdot 1198871119898

11988721

11988722

sdot sdot sdot 1198872119898

sdot sdot sdot sdot sdot sdot sdot sdot sdot sdot sdot sdot

1198871198961

1198871198962

sdot sdot sdot 119887119896119898

]]]

]

(6)

Then combined with the weight matrix 119882 the second-level fuzzy comprehensive evaluation matrix B can be calcu-lated as follows

B = 119882o1198771015840 = (1198871 1198872 119887

119898) (7)

where 119887119898is the membership degree of the 119898th remark in

remark set VIn this paper the first-level fuzzy comprehensive evalua-

tion matrix 119861119894is calculated as follows

1198611= 1198821198711o1198771

= (020 007 037 008 022 006)

o

[[[[[[[

[

01277 04574 04149

04255 03830 05745

02660 05745 01595

00426 05638 03936

01702 03192 05106

00213 03617 06170

]]]]]]]

]

= (01690 04679 03631)

(8)

Similarly we can obtain

1198612= (01005 04585 04310)

1198613= (01073 05905 03022)

1198614= (01128 04736 04136)

1198615= (01710 05133 03157)

(9)

Then we obtain the second-level fuzzy relationmatrix1198771015840

1198771015840=

[[[[[

[

01690 04679 03631

01005 04585 04310

01073 05905 03022

01128 04736 04136

01710 05133 03157

]]]]]

]

(10)

The second-level fuzzy comprehensive evaluation matrixB can be calculated as follows

B = 119882o1198771015840

= (020 022 015 012 031)

o[[[[[

[

01690 04679 03631

01005 04585 04310

01073 05905 03022

01128 04736 04136

01710 05133 03157

]]]]]

]

= (01385 04990 03603)

(11)

47 Step 7 Rate and Conclude the Grade Level Accordingto the maximum membership degree principle when 119887

1198940=

max 119887119894(1 le 119894 le 119898) we can judge that the evaluated object

belongs to the 1198940grade

In this paper since 1198872

= max 119887119894(1 le 119894 le 3) =

04990 it is shown that the risk grade of ldquoZhejiang-FuzhourdquoUHV power transmission construction project belongs toldquomoderaterdquo which means the occurrence probability of thisproject risk is medium and the risk occurrence will causegeneral loss So it is necessary for the project managers to

Mathematical Problems in Engineering 11

Table 8 Judgment matrixes and weights of ldquosociety riskrdquo criteria

Society risk 11986234

11986235

11986236

11986237

11986238

11986239

Local weight11986234

1 23 12 18 2 3 02911986235

043 1 05 08 09 13 01211986236

083 2 1 15 17 25 02411986237

056 125 067 1 11 17 01611986238

05 011 059 091 1 15 01011986239

033 077 04 059 067 1 009120582max = 59109 CI = minus00178 CR = minus00141 lt 01

Table 9 The value of RI

119899 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15RI 0 052 089 112 126 136 141 145 149 152 154 156 157 158

carry out some specific risk control measures to make theconstruction of this project run successfully

At the meantime valuing the evaluation result of indi-cators in criteria layer in centesimal form can help projectmanagers to analyze the project riskmore efficiently Supposethe comment set V = [V

1 V2 V3] = 90 50 10 and then

the centesimal value of each indicator in criteria layer can becalculated as follows

1198801= 01690 times 90 + 04679 times 50 + 03631 times 10

= 422383

1198802= 01005 times 90 + 04585 times 50 + 04310 times 10

= 362830

1198803= 01073 times 90 + 05905 times 50 + 03022 times 10

= 422

1198804= 01128 times 90 + 04736 times 50 + 04136 times 10

= 379660

1198805= 01710 times 90 + 05133 times 50 + 03157 times 10

= 442085

(12)

The centesimal value (119880) of risk evaluation of ldquoZhejiang-Fuzhourdquo UHV power transmission construction project canbe calculated as

119880 = 01385 times 90 + 04990 times 50 + 03603 times 10

= 410205

(13)

Figure 8 compares the centesimal value of each indicatorin criteria layer and we can see

1198805≻ 1198801≻ 1198803≻ 119880 ≻ 119880

4≻ 1198802 (14)

Therefore the centesimal value of ldquosociety riskrdquo is thehighest followed by ldquopolicy and law riskrdquo ldquotechnology riskrdquoldquonatural environmental riskrdquo and ldquomanagement riskrdquo Thecentesimal values of both ldquomanagement riskrdquo and ldquonatural

422383

36283

422

37966

442085

Policy and law

Management

Technology

Natural environmental

Society

Centesimal value

Centesimal value of U

risk

risk

risk

risk

risk0 5 10 15 20 25 30 35 40 45 50

Figure 8 Centesimal value of each indicator in criteria layer

environmental riskrdquo are lower than that of the project119880 whilethe centesimal values of other three indicators are larger thanthat of the project 119880 The criteria ldquoSociety riskrdquo ldquopolicy andlaw riskrdquo and ldquotechnology riskrdquo should be paidmore attentionin the risk management and control for ldquoZhejiang-FuzhourdquoUHV power transmission construction project

5 Risk Control Recommendations

According to the risk evaluation result we should paymore attention to ldquosociety riskrdquo ldquopolicy and law riskrdquo andldquotechnology riskrdquoThe specific risk control recommendationsare as follows

51 Risk Control Recommendations for ldquoSociety Riskrdquo

(1) Before and during the construction of ldquoZhejiang-Fuzhourdquo UHV power transmission project the pro-paganda work should be done in the form of TVradio newspapers brochures and so on The con-struction significance and engineering safety knowl-edge related to this project should be propagandizedin order to eliminate the worries from society fol-lowers and local villagers about this UHV powertransmission project

12 Mathematical Problems in Engineering

Table 10 The weight of risk indicators

Criteria layer Index layerIndicator Weight (119882) Indicator Local weight (119882

119871) Global weight (119882

119866)

Policy and law risk (1198801) 020

1198621

020 004001198622

007 001401198623

037 007401198624

008 001601198625

022 004401198626

006 00120

Management risk (1198802) 022

1198627

003 000661198628

007 001541198629

009 0019811986210

006 0013211986211

004 0008811986212

011 0024211986213

009 0019811986214

006 0013211986215

012 0026411986216

009 0019811986217

003 0006611986218

005 0011011986219

004 0008811986220

004 0008811986221

004 0008811986222

003 00066

Technology risk (1198803) 015

11986223

014 0021011986224

020 0030011986225

007 0010511986226

006 0009011986227

011 0016511986228

009 0013511986229

013 0019511986230

014 0021011986231

006 00090

Natural environment risk (1198804) 012 119862

32064 00768

11986233

036 00432

Society risk (1198805) 031

11986234

029 0089911986235

012 0037211986236

024 0074411986237

016 0049611986238

01 0031011986239

009 00279

(2) Grid company should try to sign a contract withlocal government which strives to make the localgovernment be responsible for land requisition houserelocation and crop compensation Grid companycan also set up aworking group to coordinate with thelocal government The determination of land com-pensation standards not only abides by the relevantlaws and regulations but also takes the opinions oflocal masses into consideration

(3) The terrain and ecological resources along the projectline should be fully understood when selecting theoptimal route Having some experienced practition-ers on the team and considering the local customsare better for the route determination During theproject construction the water and soil loss as wellas deforestation should be reduced as far as possibleWhen the project is finished the vegetation should berestored timely

Mathematical Problems in Engineering 13

(4) Keep close touch with the local government andpublic security organization in order to strengthen thesecurity of project construction the ldquomass incidentsrdquosuch as petitions demagoguism and demonstrationshould be paid close attention and some relatedmeasures such as propaganda and negotiation shouldbe taken timely strengthen the project constructionmanagement and perform civilized construction andreduce the negative impacts on local residents to aminimum

52 Risk Control Recommendations for ldquoPolicy and Law Riskrdquo

(1) The project-related personnel especially the projectmanagers should carefully study the policies andlaws related to land management deforestation loanand environmental protection and the related legalcounsel should be engaged in order to reduce the legalrisk during the project construction

(2) Strengthen the research on the policies and guidancedocuments related to energy development and plan-ning

(3) Strengthen the communication with the governmentdepartment to improve the efficiency of project exam-ination and approval

(4) Because the size and weight of UHV equipment arebigger and heavier the traffic laws and regulationsshould be carefully studied to avoid the conflictrelated to UHV equipment transportation Trans-portation limitations should be taken into considera-tion when selecting the UHV equipment and surveyon the transport route is very necessary

53 Risk Control Recommendations for ldquoTechnology Riskrdquo

(1) Track the meteorological information timely andarrange the construction plan according to theweather condition some necessary measures shouldbe taken to protect the equipment from rainwatersuch as building the temporary drain and increasingthe pumping equipment

(2) The earth-rock excavation should keep a reasonableproportion based on the quantity calculation

(3) For waterway transport due to the constant changeof shipping lane the simulation navigation shouldbe performed six months in advance to ensure thetransportation safety

(4) Measure the earth resistivity and design the ground-ing grid establish special subjects to study the impactsof ground resistance on UHVGIS equipment and theoperation of control and protection system

(5) Design the crossing construction based on differ-ent crossing facilities to reduce the risk and diffi-culty when crossing the electricity lines the crossingscheme should be designed at the design stage and

take the terrain characteristic along the project lineinto consideration

(6) The material transport plan should take weather andtransportation environment into consideration opti-mize the use of different transportation facilities andmake the fullest use of crawler-transporter vehicleand cableway

6 Conclusions

In this paper a hybrid evaluation model based on AHPand FCE method is implemented to evaluate the risk ofldquoZhejiang-Fuzhourdquo UHV power transmission constructionprojectThis hybrid evaluationmodel takes full advantages ofAHP and FCEmethod After the risk evaluation index systemis built the AHP is used to determine the index weightand FCE method is used to evaluate the project risk Finallythe specific risk control recommendations are proposed Themain results of risk evaluation of ldquoZhejiang-Fuzhourdquo UHVpower transmission construction project are as follows

(1) The risk grade of ldquoZhejiang-Fuzhourdquo UHV powertransmission construction project belongs to ldquomod-eraterdquo which indicates the occurrence probability ofproject risk is medium and the risk occurrence willcause general loss

(2) ldquoSociety riskrdquo has the highest level and the next isldquopolicy and law riskrdquo ldquotechnique riskrdquo ldquonatural envi-ronmental riskrdquo and ldquomanagement riskrdquo respectivelyldquosociety riskrdquo ldquopolicy and law riskrdquo and ldquotechnologyriskrdquo should be paid more attention in the risk man-agement and control for ldquoZhejiang-Fuzhourdquo UHVpower transmission construction project

(3) Risk control recommendations for main risk criteriawhich include society risk policy and law risk andtechnology risk are proposed

(4) This hybrid evaluation model is feasible and effectivewhich can effectively evaluate the risk of UHV powertransmission construction project

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

This study is supported by the Humanity and Social Scienceproject of the Ministry of Education of China (Project no11YJA790217) and the National Natural Science Foundationof China (Project no 71373076)

References

[1] J P Liu D X Niu and X H Song ldquoThe energy supply anddemand pattern of China a review of evolution and sustainabledevelopmentrdquo Renewable and Sustainable Energy Reviews vol25 pp 220ndash228 2013

14 Mathematical Problems in Engineering

[2] C C Lin C H Yang and J Z Shyua ldquoA comparison ofinnovation policy in the smart grid industry across the pacificchina and the USArdquo Energy Policy vol 57 pp 119ndash132 2013

[3] M Bolinger and R Wiser ldquoA comparative analysis of businessstructures suitable for farmer-ownedwind power projects in theUnited Statesrdquo Energy Policy vol 34 no 14 pp 1750ndash1761 2006

[4] S Grassi N Chokani and R S Abhari ldquoLarge scale technicaland economical assessment of wind energy potential with a GIStool case study Iowardquo Energy Policy vol 45 pp 73ndash85 2012

[5] MHellstrom I Ruuska KWikstrom andD Jafs ldquoProject gov-ernance and path creation in the early stages of Finnish nuclearpower projectsrdquo International Journal of Project Managementvol 31 no 5 pp 712ndash723 2013

[6] P Baumann and G Stevanella ldquoFish passage principles to beconsidered for medium and large dams the case study of afish passage concept for a hydroelectric power project on theMekong mainstem in Laosrdquo Ecological Engineering vol 48 pp79ndash85 2012

[7] W Amatayakul and G Berndes ldquoDetermining factor for thedevelopment of CDM biomass power projectsrdquo Energy forSustainable Development vol 16 pp 197ndash203 2012

[8] J L Liu Q X Li and Y H Wang ldquoRisk analysis in ultradeep scientific drilling project-A fuzzy synthetic evaluationapproachrdquo International Journal of Project Management vol 31no 3 pp 449ndash458 2013

[9] A Badri S Nadeau and A Gbodossou ldquoA new practicalapproach to risk management for underground mining projectin Quebecrdquo Journal of Loss Prevention in the Process Industriesvol 26 no 6 pp 1145ndash1158 2013

[10] J B Song D R Song X Q Zhang and Y Sun ldquoRiskidentification for PPP waste-to-energy incineration projects inChinardquo Energy Policy vol 61 pp 953ndash962 2013

[11] Y Hu J F Du X Z Zhang et al ldquoAn integrative frameworkfor intelligent software project risk planningrdquo Decision SupportSystems vol 55 no 4 pp 927ndash937 2013

[12] T L Saaty The Analytic Hierarchy Process McGraw-Hill NewYork NY USA 1980

[13] M P Amiri ldquoProject selection for oil-fields development byusing the AHP and fuzzy TOPSIS methodsrdquo Expert Systemswith Applications vol 37 no 9 pp 6218ndash6224 2010

[14] H Z Li and S Guo ldquoExternal economies evaluation of windpower engineering project based on analytic hierarchy processand matter-element extension modelrdquo Mathematical Problemsin Engineering vol 2013 Article ID 848901 11 pages 2013

[15] F-G Chen H-L Yao andW-G Shi ldquoApplication of fuzzy andsynthetic judgment to risk assessment of dammed lakerdquo Journalof Shanghai Jiaotong University vol 45 no 1 pp 67ndash75 2011

[16] K Fang B-F He M Yang and Z-C Wang ldquoApplication offuzzy comprehensive evaluation method to CENSrdquo Journal ofHarbin Institute of Technology vol 43 no 5 pp 30ndash36 2011

Submit your manuscripts athttpwwwhindawicom

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mathematical Problems in Engineering

Hindawi Publishing Corporationhttpwwwhindawicom

Differential EquationsInternational Journal of

Volume 2014

Applied MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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Mathematical PhysicsAdvances in

Complex AnalysisJournal of

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OptimizationJournal of

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CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

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Operations ResearchAdvances in

Journal of

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Function Spaces

Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of Mathematics and Mathematical Sciences

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The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

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Discrete Dynamics in Nature and Society

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Decision SciencesAdvances in

Discrete MathematicsJournal of

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Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Stochastic AnalysisInternational Journal of

8 Mathematical Problems in Engineering

Table 3 Pairwise comparison judgment matrixes and weights in criteria layer

1198801

1198802

1198803

1198804

1198805

Weight1198801

100 090 140 180 065 0201198802

111 100 150 165 070 0221198803

071 067 100 125 045 0151198804

056 061 080 100 040 0121198805

154 143 222 250 100 031120582max = 50034 CI = 000084 CR = 000075 lt 01

Table 4 Judgment matrixes and weights of ldquopolicy and law riskrdquo criteria

Policy and law risk 1198621

1198622

1198623

1198624

1198625

1198626

Local weight1198621

100 300 050 250 080 350 0201198622

033 100 020 090 033 120 0071198623

200 500 100 450 200 520 0371198624

040 111 022 100 030 160 0081198625

125 300 050 333 100 320 0221198626

029 083 019 063 031 100 006120582max = 60297 CI = 00059 CR = 00048 lt 01

Table 5 Judgment matrixes and weights of ldquomanagement riskrdquo criteria

Managementrisk 119862

71198628

1198629

11986210

11986211

11986212

11986213

11986214

11986215

11986216

11986217

11986218

11986219

11986220

11986221

11986222 Local weight

1198627

100 033 029 050 067 025 028 050 024 028 091 056 077 083 083 091 003

1198628

300 100 091 120 150 067 071 130 040 067 250 180 200 220 230 250 007

1198629

350 110 100 150 250 083 100 150 083 100 250 200 260 280 280 300 009

11986210

200 083 067 100 120 050 056 100 045 067 150 120 150 160 160 180 006

11986211

150 067 040 083 100 033 045 077 029 040 130 083 110 120 120 130 004

11986212

400 150 120 200 300 100 120 180 083 120 320 200 280 300 300 320 011

11986213

360 140 100 180 220 083 100 160 083 100 280 180 220 230 230 250 009

11986214

200 077 067 100 130 056 063 100 050 056 180 110 150 160 160 180 006

11986215

420 250 120 220 350 120 120 200 100 120 400 220 300 320 320 350 012

11986216

360 150 100 150 250 083 100 180 083 100 250 180 220 240 240 250 009

11986217

110 040 040 067 077 031 036 056 025 040 100 067 083 091 091 100 003

11986218

180 056 050 083 120 050 056 091 045 056 150 100 150 160 160 180 005

11986219

130 050 038 067 091 036 045 067 033 045 120 067 100 120 120 110 004

11986220

120 045 036 063 083 033 043 063 031 042 110 063 083 100 100 110 004

11986221

120 043 036 063 083 033 043 063 031 042 110 063 083 100 100 110 004

11986222

110 04 033 056 077 031 040 056 029 040 100 056 091 091 091 100 003120582max = 16055 CI = 0003697 CR = 00023 lt 01

method The eigenvector of judgment matrix with the max-imum eigenvalue is the weight vector of risk index whichdenotes the relative importance of indicators in the same levelwith regard to the indicators in the upper layer The weightvector of risk index is the relative importance of indicators

with regard to the upper layer indicator which is also calledthe local weight

In this paper the weights of indictors in criteria layer andlocal weights of indicators in index layer are calculated whichare lists in Tables 3ndash8 respectively

Mathematical Problems in Engineering 9

Table 6 Judgment matrixes and weights of ldquotechnology riskrdquo criteria

Technology risk 11986223

11986224

11986225

11986226

11986227

11986228

11986229

11986230

11986231

Local weight11986223

100 067 222 222 125 167 111 100 250 01411986224

150 100 286 333 167 250 143 133 333 02011986225

045 035 100 111 059 080 056 050 125 00711986226

045 030 090 100 056 071 050 045 111 00611986227

080 060 170 180 100 133 083 080 200 01111986228

060 040 125 140 075 100 067 067 143 00911986229

090 070 180 200 120 150 100 091 222 01311986230

100 075 200 220 125 150 110 100 250 01411986231

040 030 080 090 050 070 045 040 100 006120582max = 900585 CI = 0000731 CR = 0000504 lt 01

Table 7 Judgment matrixes and weights of ldquonatural environmentriskrdquo criteria

Natural environment risk 11986232

11986233

Local weight11986232

1 18 06411986233

056 1 036120582max = 2 CI = 0 CR = 0 lt 01

444 Substep 4 Consistency Test The consistency of relativeimportance judgment on each indicator made by expertsand engineers is the key prerequisite for using the AHP todetermine the weights of risk indicators Hence it is verynecessary to test the consistency of judgment matrix Whenthe consistency of judgmentmatrix is satisfied themaximumeigenvalue of the judgmentmatrix120582max should be equal to thenumber of indicators which are related to two consistencytest indices namely CI and CR

Consistency index (CI) which measures the divergenceof judgment matrix away from the consistency is defined asfollows

CI =120582max minus 119899

119899 minus 1 (1)

where 119899 represents the number of indicesThus the consistency ratio (CR) is defined as follows

CR =CIRI

(2)

RI is the random consistency index which is the averagevalue of eigenvalues obtained by calculating the judgmentmatrix for more than 500 times The value of RI is given inTable 9

If CR lt 01 the weight vector is acceptable otherwisethe modification of the pairwise judgment matrix is needed

As listed in the last row in Tables 3ndash8 respectivelyall the pairwise comparison judgment matrixes satisfy theconsistency test

445 Substep 5 Calculate the Index Weight The globalweight of each indicator can be determined by multiplying

the local weight of the indicator with theweight of upper layerindicator which locates in the parent node above it

The local and global weights of each risk indicator inindex layer and the weight of each indicator in criteria layerare calculated which are listed in Table 10

45 Step 5 Calculate the Fuzzy Relation Matrix Accordingto the statistical result of the questionnaire by using a certainmathematical method such as frequency-based method andweighted averagemethod the first-level fuzzy relationmatrixR can be calculated as follows

R = (119903119894119895)119899times119898

=

[[[[

[

11990311

11990312

1199031119898

11990321

11990322

1199032119898

1199031198991

1199031198992

119903119899119898

]]]]

]

(3)

where 119903119894119895is the membership degree of the 119895th remark in

remark set V for the indicator 119894 119894 = 1 2 119899 119895 =

1 2 119898 119899 is the number of indices and 119898 is the numberof risk grades in remark set V Different rows in the fuzzyrelation matrix R reflect the different membership degrees ofevaluated object subject to fuzzy set of each grade consideringdifferent evaluation indices

The frequency-based method is used to establish thefuzzy relation matrix in this paper the principle of which isif the number of experts and engineers who judge the ldquohighriskrdquo ldquomoderate riskrdquo and ldquolow riskrdquo is119898

1 1198982 and119898

3respec-

tively then the set (1198981sum3

119896=1119898119896 1198982sum3

119896=1119898119896 1198983sum3

119896=1119898119896)

is the membership set of the evaluation index The obtainedfrequency of each indicator with different risk grades is listedin Figure 7

Thus the first-level fuzzy relation matrix R can becalculated just as follows

1198771=

[[[[[[[

[

01277 04574 04149

04255 03830 05745

02660 05745 01595

00426 05638 03936

01702 03192 05106

00213 03617 06170

]]]]]]]

]

10 Mathematical Problems in Engineering

1198772=

[[[[[[[[[[[[[[[[[[[[[[[[[[

[

00106 04362 05532

00957 04894 04149

01170 05532 03298

00957 03298 05745

00638 04681 04681

01489 03617 04894

01383 04894 03723

00745 04787 04468

01596 03723 04681

01170 06915 01915

00426 04574 05000

00851 03830 05319

00532 04681 04787

00426 04149 05425

00426 04574 05000

00213 05638 04149

]]]]]]]]]]]]]]]]]]]]]]]]]]

]

1198773=

[[[[[[[[[[[[

[

01170 04787 04043

02021 04149 03830

00638 04575 04787

00532 04255 05213

00851 07447 01702

00638 07766 01596

00851 08404 00745

00958 07340 01702

00532 03191 06277

]]]]]]]]]]]]

]

1198774= [

01702 04468 03830

00106 05213 04681]

1198775=

[[[[[[[

[

02447 05638 01915

00957 05000 04043

02340 04787 02872

01064 04894 04042

00957 04681 04362

00638 05532 03830

]]]]]]]

]

(4)

46 Step 6 Make Fuzzy Composition Synthesize the first-level fuzzy relation matrix R with the local weight 119882

119871 and

then the membership matrix 119861119894could be obtained which is

call the first-level fuzzy comprehensive evaluation matrix

119861119894= 119882119871o119877 = (119887

1198941 1198871198942 119887

119894119898) (5)

Due to the hierarchical structure of the evaluation indexsystem the second-level fuzzy relation matrix 119877

1015840 needs to becalculated

1198771015840=

[[[[

[

1198611

1198612

119861119896

]]]]

]

=[[[

[

11988711

11988712

sdot sdot sdot 1198871119898

11988721

11988722

sdot sdot sdot 1198872119898

sdot sdot sdot sdot sdot sdot sdot sdot sdot sdot sdot sdot

1198871198961

1198871198962

sdot sdot sdot 119887119896119898

]]]

]

(6)

Then combined with the weight matrix 119882 the second-level fuzzy comprehensive evaluation matrix B can be calcu-lated as follows

B = 119882o1198771015840 = (1198871 1198872 119887

119898) (7)

where 119887119898is the membership degree of the 119898th remark in

remark set VIn this paper the first-level fuzzy comprehensive evalua-

tion matrix 119861119894is calculated as follows

1198611= 1198821198711o1198771

= (020 007 037 008 022 006)

o

[[[[[[[

[

01277 04574 04149

04255 03830 05745

02660 05745 01595

00426 05638 03936

01702 03192 05106

00213 03617 06170

]]]]]]]

]

= (01690 04679 03631)

(8)

Similarly we can obtain

1198612= (01005 04585 04310)

1198613= (01073 05905 03022)

1198614= (01128 04736 04136)

1198615= (01710 05133 03157)

(9)

Then we obtain the second-level fuzzy relationmatrix1198771015840

1198771015840=

[[[[[

[

01690 04679 03631

01005 04585 04310

01073 05905 03022

01128 04736 04136

01710 05133 03157

]]]]]

]

(10)

The second-level fuzzy comprehensive evaluation matrixB can be calculated as follows

B = 119882o1198771015840

= (020 022 015 012 031)

o[[[[[

[

01690 04679 03631

01005 04585 04310

01073 05905 03022

01128 04736 04136

01710 05133 03157

]]]]]

]

= (01385 04990 03603)

(11)

47 Step 7 Rate and Conclude the Grade Level Accordingto the maximum membership degree principle when 119887

1198940=

max 119887119894(1 le 119894 le 119898) we can judge that the evaluated object

belongs to the 1198940grade

In this paper since 1198872

= max 119887119894(1 le 119894 le 3) =

04990 it is shown that the risk grade of ldquoZhejiang-FuzhourdquoUHV power transmission construction project belongs toldquomoderaterdquo which means the occurrence probability of thisproject risk is medium and the risk occurrence will causegeneral loss So it is necessary for the project managers to

Mathematical Problems in Engineering 11

Table 8 Judgment matrixes and weights of ldquosociety riskrdquo criteria

Society risk 11986234

11986235

11986236

11986237

11986238

11986239

Local weight11986234

1 23 12 18 2 3 02911986235

043 1 05 08 09 13 01211986236

083 2 1 15 17 25 02411986237

056 125 067 1 11 17 01611986238

05 011 059 091 1 15 01011986239

033 077 04 059 067 1 009120582max = 59109 CI = minus00178 CR = minus00141 lt 01

Table 9 The value of RI

119899 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15RI 0 052 089 112 126 136 141 145 149 152 154 156 157 158

carry out some specific risk control measures to make theconstruction of this project run successfully

At the meantime valuing the evaluation result of indi-cators in criteria layer in centesimal form can help projectmanagers to analyze the project riskmore efficiently Supposethe comment set V = [V

1 V2 V3] = 90 50 10 and then

the centesimal value of each indicator in criteria layer can becalculated as follows

1198801= 01690 times 90 + 04679 times 50 + 03631 times 10

= 422383

1198802= 01005 times 90 + 04585 times 50 + 04310 times 10

= 362830

1198803= 01073 times 90 + 05905 times 50 + 03022 times 10

= 422

1198804= 01128 times 90 + 04736 times 50 + 04136 times 10

= 379660

1198805= 01710 times 90 + 05133 times 50 + 03157 times 10

= 442085

(12)

The centesimal value (119880) of risk evaluation of ldquoZhejiang-Fuzhourdquo UHV power transmission construction project canbe calculated as

119880 = 01385 times 90 + 04990 times 50 + 03603 times 10

= 410205

(13)

Figure 8 compares the centesimal value of each indicatorin criteria layer and we can see

1198805≻ 1198801≻ 1198803≻ 119880 ≻ 119880

4≻ 1198802 (14)

Therefore the centesimal value of ldquosociety riskrdquo is thehighest followed by ldquopolicy and law riskrdquo ldquotechnology riskrdquoldquonatural environmental riskrdquo and ldquomanagement riskrdquo Thecentesimal values of both ldquomanagement riskrdquo and ldquonatural

422383

36283

422

37966

442085

Policy and law

Management

Technology

Natural environmental

Society

Centesimal value

Centesimal value of U

risk

risk

risk

risk

risk0 5 10 15 20 25 30 35 40 45 50

Figure 8 Centesimal value of each indicator in criteria layer

environmental riskrdquo are lower than that of the project119880 whilethe centesimal values of other three indicators are larger thanthat of the project 119880 The criteria ldquoSociety riskrdquo ldquopolicy andlaw riskrdquo and ldquotechnology riskrdquo should be paidmore attentionin the risk management and control for ldquoZhejiang-FuzhourdquoUHV power transmission construction project

5 Risk Control Recommendations

According to the risk evaluation result we should paymore attention to ldquosociety riskrdquo ldquopolicy and law riskrdquo andldquotechnology riskrdquoThe specific risk control recommendationsare as follows

51 Risk Control Recommendations for ldquoSociety Riskrdquo

(1) Before and during the construction of ldquoZhejiang-Fuzhourdquo UHV power transmission project the pro-paganda work should be done in the form of TVradio newspapers brochures and so on The con-struction significance and engineering safety knowl-edge related to this project should be propagandizedin order to eliminate the worries from society fol-lowers and local villagers about this UHV powertransmission project

12 Mathematical Problems in Engineering

Table 10 The weight of risk indicators

Criteria layer Index layerIndicator Weight (119882) Indicator Local weight (119882

119871) Global weight (119882

119866)

Policy and law risk (1198801) 020

1198621

020 004001198622

007 001401198623

037 007401198624

008 001601198625

022 004401198626

006 00120

Management risk (1198802) 022

1198627

003 000661198628

007 001541198629

009 0019811986210

006 0013211986211

004 0008811986212

011 0024211986213

009 0019811986214

006 0013211986215

012 0026411986216

009 0019811986217

003 0006611986218

005 0011011986219

004 0008811986220

004 0008811986221

004 0008811986222

003 00066

Technology risk (1198803) 015

11986223

014 0021011986224

020 0030011986225

007 0010511986226

006 0009011986227

011 0016511986228

009 0013511986229

013 0019511986230

014 0021011986231

006 00090

Natural environment risk (1198804) 012 119862

32064 00768

11986233

036 00432

Society risk (1198805) 031

11986234

029 0089911986235

012 0037211986236

024 0074411986237

016 0049611986238

01 0031011986239

009 00279

(2) Grid company should try to sign a contract withlocal government which strives to make the localgovernment be responsible for land requisition houserelocation and crop compensation Grid companycan also set up aworking group to coordinate with thelocal government The determination of land com-pensation standards not only abides by the relevantlaws and regulations but also takes the opinions oflocal masses into consideration

(3) The terrain and ecological resources along the projectline should be fully understood when selecting theoptimal route Having some experienced practition-ers on the team and considering the local customsare better for the route determination During theproject construction the water and soil loss as wellas deforestation should be reduced as far as possibleWhen the project is finished the vegetation should berestored timely

Mathematical Problems in Engineering 13

(4) Keep close touch with the local government andpublic security organization in order to strengthen thesecurity of project construction the ldquomass incidentsrdquosuch as petitions demagoguism and demonstrationshould be paid close attention and some relatedmeasures such as propaganda and negotiation shouldbe taken timely strengthen the project constructionmanagement and perform civilized construction andreduce the negative impacts on local residents to aminimum

52 Risk Control Recommendations for ldquoPolicy and Law Riskrdquo

(1) The project-related personnel especially the projectmanagers should carefully study the policies andlaws related to land management deforestation loanand environmental protection and the related legalcounsel should be engaged in order to reduce the legalrisk during the project construction

(2) Strengthen the research on the policies and guidancedocuments related to energy development and plan-ning

(3) Strengthen the communication with the governmentdepartment to improve the efficiency of project exam-ination and approval

(4) Because the size and weight of UHV equipment arebigger and heavier the traffic laws and regulationsshould be carefully studied to avoid the conflictrelated to UHV equipment transportation Trans-portation limitations should be taken into considera-tion when selecting the UHV equipment and surveyon the transport route is very necessary

53 Risk Control Recommendations for ldquoTechnology Riskrdquo

(1) Track the meteorological information timely andarrange the construction plan according to theweather condition some necessary measures shouldbe taken to protect the equipment from rainwatersuch as building the temporary drain and increasingthe pumping equipment

(2) The earth-rock excavation should keep a reasonableproportion based on the quantity calculation

(3) For waterway transport due to the constant changeof shipping lane the simulation navigation shouldbe performed six months in advance to ensure thetransportation safety

(4) Measure the earth resistivity and design the ground-ing grid establish special subjects to study the impactsof ground resistance on UHVGIS equipment and theoperation of control and protection system

(5) Design the crossing construction based on differ-ent crossing facilities to reduce the risk and diffi-culty when crossing the electricity lines the crossingscheme should be designed at the design stage and

take the terrain characteristic along the project lineinto consideration

(6) The material transport plan should take weather andtransportation environment into consideration opti-mize the use of different transportation facilities andmake the fullest use of crawler-transporter vehicleand cableway

6 Conclusions

In this paper a hybrid evaluation model based on AHPand FCE method is implemented to evaluate the risk ofldquoZhejiang-Fuzhourdquo UHV power transmission constructionprojectThis hybrid evaluationmodel takes full advantages ofAHP and FCEmethod After the risk evaluation index systemis built the AHP is used to determine the index weightand FCE method is used to evaluate the project risk Finallythe specific risk control recommendations are proposed Themain results of risk evaluation of ldquoZhejiang-Fuzhourdquo UHVpower transmission construction project are as follows

(1) The risk grade of ldquoZhejiang-Fuzhourdquo UHV powertransmission construction project belongs to ldquomod-eraterdquo which indicates the occurrence probability ofproject risk is medium and the risk occurrence willcause general loss

(2) ldquoSociety riskrdquo has the highest level and the next isldquopolicy and law riskrdquo ldquotechnique riskrdquo ldquonatural envi-ronmental riskrdquo and ldquomanagement riskrdquo respectivelyldquosociety riskrdquo ldquopolicy and law riskrdquo and ldquotechnologyriskrdquo should be paid more attention in the risk man-agement and control for ldquoZhejiang-Fuzhourdquo UHVpower transmission construction project

(3) Risk control recommendations for main risk criteriawhich include society risk policy and law risk andtechnology risk are proposed

(4) This hybrid evaluation model is feasible and effectivewhich can effectively evaluate the risk of UHV powertransmission construction project

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

This study is supported by the Humanity and Social Scienceproject of the Ministry of Education of China (Project no11YJA790217) and the National Natural Science Foundationof China (Project no 71373076)

References

[1] J P Liu D X Niu and X H Song ldquoThe energy supply anddemand pattern of China a review of evolution and sustainabledevelopmentrdquo Renewable and Sustainable Energy Reviews vol25 pp 220ndash228 2013

14 Mathematical Problems in Engineering

[2] C C Lin C H Yang and J Z Shyua ldquoA comparison ofinnovation policy in the smart grid industry across the pacificchina and the USArdquo Energy Policy vol 57 pp 119ndash132 2013

[3] M Bolinger and R Wiser ldquoA comparative analysis of businessstructures suitable for farmer-ownedwind power projects in theUnited Statesrdquo Energy Policy vol 34 no 14 pp 1750ndash1761 2006

[4] S Grassi N Chokani and R S Abhari ldquoLarge scale technicaland economical assessment of wind energy potential with a GIStool case study Iowardquo Energy Policy vol 45 pp 73ndash85 2012

[5] MHellstrom I Ruuska KWikstrom andD Jafs ldquoProject gov-ernance and path creation in the early stages of Finnish nuclearpower projectsrdquo International Journal of Project Managementvol 31 no 5 pp 712ndash723 2013

[6] P Baumann and G Stevanella ldquoFish passage principles to beconsidered for medium and large dams the case study of afish passage concept for a hydroelectric power project on theMekong mainstem in Laosrdquo Ecological Engineering vol 48 pp79ndash85 2012

[7] W Amatayakul and G Berndes ldquoDetermining factor for thedevelopment of CDM biomass power projectsrdquo Energy forSustainable Development vol 16 pp 197ndash203 2012

[8] J L Liu Q X Li and Y H Wang ldquoRisk analysis in ultradeep scientific drilling project-A fuzzy synthetic evaluationapproachrdquo International Journal of Project Management vol 31no 3 pp 449ndash458 2013

[9] A Badri S Nadeau and A Gbodossou ldquoA new practicalapproach to risk management for underground mining projectin Quebecrdquo Journal of Loss Prevention in the Process Industriesvol 26 no 6 pp 1145ndash1158 2013

[10] J B Song D R Song X Q Zhang and Y Sun ldquoRiskidentification for PPP waste-to-energy incineration projects inChinardquo Energy Policy vol 61 pp 953ndash962 2013

[11] Y Hu J F Du X Z Zhang et al ldquoAn integrative frameworkfor intelligent software project risk planningrdquo Decision SupportSystems vol 55 no 4 pp 927ndash937 2013

[12] T L Saaty The Analytic Hierarchy Process McGraw-Hill NewYork NY USA 1980

[13] M P Amiri ldquoProject selection for oil-fields development byusing the AHP and fuzzy TOPSIS methodsrdquo Expert Systemswith Applications vol 37 no 9 pp 6218ndash6224 2010

[14] H Z Li and S Guo ldquoExternal economies evaluation of windpower engineering project based on analytic hierarchy processand matter-element extension modelrdquo Mathematical Problemsin Engineering vol 2013 Article ID 848901 11 pages 2013

[15] F-G Chen H-L Yao andW-G Shi ldquoApplication of fuzzy andsynthetic judgment to risk assessment of dammed lakerdquo Journalof Shanghai Jiaotong University vol 45 no 1 pp 67ndash75 2011

[16] K Fang B-F He M Yang and Z-C Wang ldquoApplication offuzzy comprehensive evaluation method to CENSrdquo Journal ofHarbin Institute of Technology vol 43 no 5 pp 30ndash36 2011

Submit your manuscripts athttpwwwhindawicom

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mathematical Problems in Engineering

Hindawi Publishing Corporationhttpwwwhindawicom

Differential EquationsInternational Journal of

Volume 2014

Applied MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mathematical PhysicsAdvances in

Complex AnalysisJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

OptimizationJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Operations ResearchAdvances in

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Function Spaces

Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of Mathematics and Mathematical Sciences

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Algebra

Discrete Dynamics in Nature and Society

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Decision SciencesAdvances in

Discrete MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom

Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Stochastic AnalysisInternational Journal of

Mathematical Problems in Engineering 9

Table 6 Judgment matrixes and weights of ldquotechnology riskrdquo criteria

Technology risk 11986223

11986224

11986225

11986226

11986227

11986228

11986229

11986230

11986231

Local weight11986223

100 067 222 222 125 167 111 100 250 01411986224

150 100 286 333 167 250 143 133 333 02011986225

045 035 100 111 059 080 056 050 125 00711986226

045 030 090 100 056 071 050 045 111 00611986227

080 060 170 180 100 133 083 080 200 01111986228

060 040 125 140 075 100 067 067 143 00911986229

090 070 180 200 120 150 100 091 222 01311986230

100 075 200 220 125 150 110 100 250 01411986231

040 030 080 090 050 070 045 040 100 006120582max = 900585 CI = 0000731 CR = 0000504 lt 01

Table 7 Judgment matrixes and weights of ldquonatural environmentriskrdquo criteria

Natural environment risk 11986232

11986233

Local weight11986232

1 18 06411986233

056 1 036120582max = 2 CI = 0 CR = 0 lt 01

444 Substep 4 Consistency Test The consistency of relativeimportance judgment on each indicator made by expertsand engineers is the key prerequisite for using the AHP todetermine the weights of risk indicators Hence it is verynecessary to test the consistency of judgment matrix Whenthe consistency of judgmentmatrix is satisfied themaximumeigenvalue of the judgmentmatrix120582max should be equal to thenumber of indicators which are related to two consistencytest indices namely CI and CR

Consistency index (CI) which measures the divergenceof judgment matrix away from the consistency is defined asfollows

CI =120582max minus 119899

119899 minus 1 (1)

where 119899 represents the number of indicesThus the consistency ratio (CR) is defined as follows

CR =CIRI

(2)

RI is the random consistency index which is the averagevalue of eigenvalues obtained by calculating the judgmentmatrix for more than 500 times The value of RI is given inTable 9

If CR lt 01 the weight vector is acceptable otherwisethe modification of the pairwise judgment matrix is needed

As listed in the last row in Tables 3ndash8 respectivelyall the pairwise comparison judgment matrixes satisfy theconsistency test

445 Substep 5 Calculate the Index Weight The globalweight of each indicator can be determined by multiplying

the local weight of the indicator with theweight of upper layerindicator which locates in the parent node above it

The local and global weights of each risk indicator inindex layer and the weight of each indicator in criteria layerare calculated which are listed in Table 10

45 Step 5 Calculate the Fuzzy Relation Matrix Accordingto the statistical result of the questionnaire by using a certainmathematical method such as frequency-based method andweighted averagemethod the first-level fuzzy relationmatrixR can be calculated as follows

R = (119903119894119895)119899times119898

=

[[[[

[

11990311

11990312

1199031119898

11990321

11990322

1199032119898

1199031198991

1199031198992

119903119899119898

]]]]

]

(3)

where 119903119894119895is the membership degree of the 119895th remark in

remark set V for the indicator 119894 119894 = 1 2 119899 119895 =

1 2 119898 119899 is the number of indices and 119898 is the numberof risk grades in remark set V Different rows in the fuzzyrelation matrix R reflect the different membership degrees ofevaluated object subject to fuzzy set of each grade consideringdifferent evaluation indices

The frequency-based method is used to establish thefuzzy relation matrix in this paper the principle of which isif the number of experts and engineers who judge the ldquohighriskrdquo ldquomoderate riskrdquo and ldquolow riskrdquo is119898

1 1198982 and119898

3respec-

tively then the set (1198981sum3

119896=1119898119896 1198982sum3

119896=1119898119896 1198983sum3

119896=1119898119896)

is the membership set of the evaluation index The obtainedfrequency of each indicator with different risk grades is listedin Figure 7

Thus the first-level fuzzy relation matrix R can becalculated just as follows

1198771=

[[[[[[[

[

01277 04574 04149

04255 03830 05745

02660 05745 01595

00426 05638 03936

01702 03192 05106

00213 03617 06170

]]]]]]]

]

10 Mathematical Problems in Engineering

1198772=

[[[[[[[[[[[[[[[[[[[[[[[[[[

[

00106 04362 05532

00957 04894 04149

01170 05532 03298

00957 03298 05745

00638 04681 04681

01489 03617 04894

01383 04894 03723

00745 04787 04468

01596 03723 04681

01170 06915 01915

00426 04574 05000

00851 03830 05319

00532 04681 04787

00426 04149 05425

00426 04574 05000

00213 05638 04149

]]]]]]]]]]]]]]]]]]]]]]]]]]

]

1198773=

[[[[[[[[[[[[

[

01170 04787 04043

02021 04149 03830

00638 04575 04787

00532 04255 05213

00851 07447 01702

00638 07766 01596

00851 08404 00745

00958 07340 01702

00532 03191 06277

]]]]]]]]]]]]

]

1198774= [

01702 04468 03830

00106 05213 04681]

1198775=

[[[[[[[

[

02447 05638 01915

00957 05000 04043

02340 04787 02872

01064 04894 04042

00957 04681 04362

00638 05532 03830

]]]]]]]

]

(4)

46 Step 6 Make Fuzzy Composition Synthesize the first-level fuzzy relation matrix R with the local weight 119882

119871 and

then the membership matrix 119861119894could be obtained which is

call the first-level fuzzy comprehensive evaluation matrix

119861119894= 119882119871o119877 = (119887

1198941 1198871198942 119887

119894119898) (5)

Due to the hierarchical structure of the evaluation indexsystem the second-level fuzzy relation matrix 119877

1015840 needs to becalculated

1198771015840=

[[[[

[

1198611

1198612

119861119896

]]]]

]

=[[[

[

11988711

11988712

sdot sdot sdot 1198871119898

11988721

11988722

sdot sdot sdot 1198872119898

sdot sdot sdot sdot sdot sdot sdot sdot sdot sdot sdot sdot

1198871198961

1198871198962

sdot sdot sdot 119887119896119898

]]]

]

(6)

Then combined with the weight matrix 119882 the second-level fuzzy comprehensive evaluation matrix B can be calcu-lated as follows

B = 119882o1198771015840 = (1198871 1198872 119887

119898) (7)

where 119887119898is the membership degree of the 119898th remark in

remark set VIn this paper the first-level fuzzy comprehensive evalua-

tion matrix 119861119894is calculated as follows

1198611= 1198821198711o1198771

= (020 007 037 008 022 006)

o

[[[[[[[

[

01277 04574 04149

04255 03830 05745

02660 05745 01595

00426 05638 03936

01702 03192 05106

00213 03617 06170

]]]]]]]

]

= (01690 04679 03631)

(8)

Similarly we can obtain

1198612= (01005 04585 04310)

1198613= (01073 05905 03022)

1198614= (01128 04736 04136)

1198615= (01710 05133 03157)

(9)

Then we obtain the second-level fuzzy relationmatrix1198771015840

1198771015840=

[[[[[

[

01690 04679 03631

01005 04585 04310

01073 05905 03022

01128 04736 04136

01710 05133 03157

]]]]]

]

(10)

The second-level fuzzy comprehensive evaluation matrixB can be calculated as follows

B = 119882o1198771015840

= (020 022 015 012 031)

o[[[[[

[

01690 04679 03631

01005 04585 04310

01073 05905 03022

01128 04736 04136

01710 05133 03157

]]]]]

]

= (01385 04990 03603)

(11)

47 Step 7 Rate and Conclude the Grade Level Accordingto the maximum membership degree principle when 119887

1198940=

max 119887119894(1 le 119894 le 119898) we can judge that the evaluated object

belongs to the 1198940grade

In this paper since 1198872

= max 119887119894(1 le 119894 le 3) =

04990 it is shown that the risk grade of ldquoZhejiang-FuzhourdquoUHV power transmission construction project belongs toldquomoderaterdquo which means the occurrence probability of thisproject risk is medium and the risk occurrence will causegeneral loss So it is necessary for the project managers to

Mathematical Problems in Engineering 11

Table 8 Judgment matrixes and weights of ldquosociety riskrdquo criteria

Society risk 11986234

11986235

11986236

11986237

11986238

11986239

Local weight11986234

1 23 12 18 2 3 02911986235

043 1 05 08 09 13 01211986236

083 2 1 15 17 25 02411986237

056 125 067 1 11 17 01611986238

05 011 059 091 1 15 01011986239

033 077 04 059 067 1 009120582max = 59109 CI = minus00178 CR = minus00141 lt 01

Table 9 The value of RI

119899 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15RI 0 052 089 112 126 136 141 145 149 152 154 156 157 158

carry out some specific risk control measures to make theconstruction of this project run successfully

At the meantime valuing the evaluation result of indi-cators in criteria layer in centesimal form can help projectmanagers to analyze the project riskmore efficiently Supposethe comment set V = [V

1 V2 V3] = 90 50 10 and then

the centesimal value of each indicator in criteria layer can becalculated as follows

1198801= 01690 times 90 + 04679 times 50 + 03631 times 10

= 422383

1198802= 01005 times 90 + 04585 times 50 + 04310 times 10

= 362830

1198803= 01073 times 90 + 05905 times 50 + 03022 times 10

= 422

1198804= 01128 times 90 + 04736 times 50 + 04136 times 10

= 379660

1198805= 01710 times 90 + 05133 times 50 + 03157 times 10

= 442085

(12)

The centesimal value (119880) of risk evaluation of ldquoZhejiang-Fuzhourdquo UHV power transmission construction project canbe calculated as

119880 = 01385 times 90 + 04990 times 50 + 03603 times 10

= 410205

(13)

Figure 8 compares the centesimal value of each indicatorin criteria layer and we can see

1198805≻ 1198801≻ 1198803≻ 119880 ≻ 119880

4≻ 1198802 (14)

Therefore the centesimal value of ldquosociety riskrdquo is thehighest followed by ldquopolicy and law riskrdquo ldquotechnology riskrdquoldquonatural environmental riskrdquo and ldquomanagement riskrdquo Thecentesimal values of both ldquomanagement riskrdquo and ldquonatural

422383

36283

422

37966

442085

Policy and law

Management

Technology

Natural environmental

Society

Centesimal value

Centesimal value of U

risk

risk

risk

risk

risk0 5 10 15 20 25 30 35 40 45 50

Figure 8 Centesimal value of each indicator in criteria layer

environmental riskrdquo are lower than that of the project119880 whilethe centesimal values of other three indicators are larger thanthat of the project 119880 The criteria ldquoSociety riskrdquo ldquopolicy andlaw riskrdquo and ldquotechnology riskrdquo should be paidmore attentionin the risk management and control for ldquoZhejiang-FuzhourdquoUHV power transmission construction project

5 Risk Control Recommendations

According to the risk evaluation result we should paymore attention to ldquosociety riskrdquo ldquopolicy and law riskrdquo andldquotechnology riskrdquoThe specific risk control recommendationsare as follows

51 Risk Control Recommendations for ldquoSociety Riskrdquo

(1) Before and during the construction of ldquoZhejiang-Fuzhourdquo UHV power transmission project the pro-paganda work should be done in the form of TVradio newspapers brochures and so on The con-struction significance and engineering safety knowl-edge related to this project should be propagandizedin order to eliminate the worries from society fol-lowers and local villagers about this UHV powertransmission project

12 Mathematical Problems in Engineering

Table 10 The weight of risk indicators

Criteria layer Index layerIndicator Weight (119882) Indicator Local weight (119882

119871) Global weight (119882

119866)

Policy and law risk (1198801) 020

1198621

020 004001198622

007 001401198623

037 007401198624

008 001601198625

022 004401198626

006 00120

Management risk (1198802) 022

1198627

003 000661198628

007 001541198629

009 0019811986210

006 0013211986211

004 0008811986212

011 0024211986213

009 0019811986214

006 0013211986215

012 0026411986216

009 0019811986217

003 0006611986218

005 0011011986219

004 0008811986220

004 0008811986221

004 0008811986222

003 00066

Technology risk (1198803) 015

11986223

014 0021011986224

020 0030011986225

007 0010511986226

006 0009011986227

011 0016511986228

009 0013511986229

013 0019511986230

014 0021011986231

006 00090

Natural environment risk (1198804) 012 119862

32064 00768

11986233

036 00432

Society risk (1198805) 031

11986234

029 0089911986235

012 0037211986236

024 0074411986237

016 0049611986238

01 0031011986239

009 00279

(2) Grid company should try to sign a contract withlocal government which strives to make the localgovernment be responsible for land requisition houserelocation and crop compensation Grid companycan also set up aworking group to coordinate with thelocal government The determination of land com-pensation standards not only abides by the relevantlaws and regulations but also takes the opinions oflocal masses into consideration

(3) The terrain and ecological resources along the projectline should be fully understood when selecting theoptimal route Having some experienced practition-ers on the team and considering the local customsare better for the route determination During theproject construction the water and soil loss as wellas deforestation should be reduced as far as possibleWhen the project is finished the vegetation should berestored timely

Mathematical Problems in Engineering 13

(4) Keep close touch with the local government andpublic security organization in order to strengthen thesecurity of project construction the ldquomass incidentsrdquosuch as petitions demagoguism and demonstrationshould be paid close attention and some relatedmeasures such as propaganda and negotiation shouldbe taken timely strengthen the project constructionmanagement and perform civilized construction andreduce the negative impacts on local residents to aminimum

52 Risk Control Recommendations for ldquoPolicy and Law Riskrdquo

(1) The project-related personnel especially the projectmanagers should carefully study the policies andlaws related to land management deforestation loanand environmental protection and the related legalcounsel should be engaged in order to reduce the legalrisk during the project construction

(2) Strengthen the research on the policies and guidancedocuments related to energy development and plan-ning

(3) Strengthen the communication with the governmentdepartment to improve the efficiency of project exam-ination and approval

(4) Because the size and weight of UHV equipment arebigger and heavier the traffic laws and regulationsshould be carefully studied to avoid the conflictrelated to UHV equipment transportation Trans-portation limitations should be taken into considera-tion when selecting the UHV equipment and surveyon the transport route is very necessary

53 Risk Control Recommendations for ldquoTechnology Riskrdquo

(1) Track the meteorological information timely andarrange the construction plan according to theweather condition some necessary measures shouldbe taken to protect the equipment from rainwatersuch as building the temporary drain and increasingthe pumping equipment

(2) The earth-rock excavation should keep a reasonableproportion based on the quantity calculation

(3) For waterway transport due to the constant changeof shipping lane the simulation navigation shouldbe performed six months in advance to ensure thetransportation safety

(4) Measure the earth resistivity and design the ground-ing grid establish special subjects to study the impactsof ground resistance on UHVGIS equipment and theoperation of control and protection system

(5) Design the crossing construction based on differ-ent crossing facilities to reduce the risk and diffi-culty when crossing the electricity lines the crossingscheme should be designed at the design stage and

take the terrain characteristic along the project lineinto consideration

(6) The material transport plan should take weather andtransportation environment into consideration opti-mize the use of different transportation facilities andmake the fullest use of crawler-transporter vehicleand cableway

6 Conclusions

In this paper a hybrid evaluation model based on AHPand FCE method is implemented to evaluate the risk ofldquoZhejiang-Fuzhourdquo UHV power transmission constructionprojectThis hybrid evaluationmodel takes full advantages ofAHP and FCEmethod After the risk evaluation index systemis built the AHP is used to determine the index weightand FCE method is used to evaluate the project risk Finallythe specific risk control recommendations are proposed Themain results of risk evaluation of ldquoZhejiang-Fuzhourdquo UHVpower transmission construction project are as follows

(1) The risk grade of ldquoZhejiang-Fuzhourdquo UHV powertransmission construction project belongs to ldquomod-eraterdquo which indicates the occurrence probability ofproject risk is medium and the risk occurrence willcause general loss

(2) ldquoSociety riskrdquo has the highest level and the next isldquopolicy and law riskrdquo ldquotechnique riskrdquo ldquonatural envi-ronmental riskrdquo and ldquomanagement riskrdquo respectivelyldquosociety riskrdquo ldquopolicy and law riskrdquo and ldquotechnologyriskrdquo should be paid more attention in the risk man-agement and control for ldquoZhejiang-Fuzhourdquo UHVpower transmission construction project

(3) Risk control recommendations for main risk criteriawhich include society risk policy and law risk andtechnology risk are proposed

(4) This hybrid evaluation model is feasible and effectivewhich can effectively evaluate the risk of UHV powertransmission construction project

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

This study is supported by the Humanity and Social Scienceproject of the Ministry of Education of China (Project no11YJA790217) and the National Natural Science Foundationof China (Project no 71373076)

References

[1] J P Liu D X Niu and X H Song ldquoThe energy supply anddemand pattern of China a review of evolution and sustainabledevelopmentrdquo Renewable and Sustainable Energy Reviews vol25 pp 220ndash228 2013

14 Mathematical Problems in Engineering

[2] C C Lin C H Yang and J Z Shyua ldquoA comparison ofinnovation policy in the smart grid industry across the pacificchina and the USArdquo Energy Policy vol 57 pp 119ndash132 2013

[3] M Bolinger and R Wiser ldquoA comparative analysis of businessstructures suitable for farmer-ownedwind power projects in theUnited Statesrdquo Energy Policy vol 34 no 14 pp 1750ndash1761 2006

[4] S Grassi N Chokani and R S Abhari ldquoLarge scale technicaland economical assessment of wind energy potential with a GIStool case study Iowardquo Energy Policy vol 45 pp 73ndash85 2012

[5] MHellstrom I Ruuska KWikstrom andD Jafs ldquoProject gov-ernance and path creation in the early stages of Finnish nuclearpower projectsrdquo International Journal of Project Managementvol 31 no 5 pp 712ndash723 2013

[6] P Baumann and G Stevanella ldquoFish passage principles to beconsidered for medium and large dams the case study of afish passage concept for a hydroelectric power project on theMekong mainstem in Laosrdquo Ecological Engineering vol 48 pp79ndash85 2012

[7] W Amatayakul and G Berndes ldquoDetermining factor for thedevelopment of CDM biomass power projectsrdquo Energy forSustainable Development vol 16 pp 197ndash203 2012

[8] J L Liu Q X Li and Y H Wang ldquoRisk analysis in ultradeep scientific drilling project-A fuzzy synthetic evaluationapproachrdquo International Journal of Project Management vol 31no 3 pp 449ndash458 2013

[9] A Badri S Nadeau and A Gbodossou ldquoA new practicalapproach to risk management for underground mining projectin Quebecrdquo Journal of Loss Prevention in the Process Industriesvol 26 no 6 pp 1145ndash1158 2013

[10] J B Song D R Song X Q Zhang and Y Sun ldquoRiskidentification for PPP waste-to-energy incineration projects inChinardquo Energy Policy vol 61 pp 953ndash962 2013

[11] Y Hu J F Du X Z Zhang et al ldquoAn integrative frameworkfor intelligent software project risk planningrdquo Decision SupportSystems vol 55 no 4 pp 927ndash937 2013

[12] T L Saaty The Analytic Hierarchy Process McGraw-Hill NewYork NY USA 1980

[13] M P Amiri ldquoProject selection for oil-fields development byusing the AHP and fuzzy TOPSIS methodsrdquo Expert Systemswith Applications vol 37 no 9 pp 6218ndash6224 2010

[14] H Z Li and S Guo ldquoExternal economies evaluation of windpower engineering project based on analytic hierarchy processand matter-element extension modelrdquo Mathematical Problemsin Engineering vol 2013 Article ID 848901 11 pages 2013

[15] F-G Chen H-L Yao andW-G Shi ldquoApplication of fuzzy andsynthetic judgment to risk assessment of dammed lakerdquo Journalof Shanghai Jiaotong University vol 45 no 1 pp 67ndash75 2011

[16] K Fang B-F He M Yang and Z-C Wang ldquoApplication offuzzy comprehensive evaluation method to CENSrdquo Journal ofHarbin Institute of Technology vol 43 no 5 pp 30ndash36 2011

Submit your manuscripts athttpwwwhindawicom

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mathematical Problems in Engineering

Hindawi Publishing Corporationhttpwwwhindawicom

Differential EquationsInternational Journal of

Volume 2014

Applied MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mathematical PhysicsAdvances in

Complex AnalysisJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

OptimizationJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Operations ResearchAdvances in

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Function Spaces

Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of Mathematics and Mathematical Sciences

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Algebra

Discrete Dynamics in Nature and Society

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Decision SciencesAdvances in

Discrete MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom

Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Stochastic AnalysisInternational Journal of

10 Mathematical Problems in Engineering

1198772=

[[[[[[[[[[[[[[[[[[[[[[[[[[

[

00106 04362 05532

00957 04894 04149

01170 05532 03298

00957 03298 05745

00638 04681 04681

01489 03617 04894

01383 04894 03723

00745 04787 04468

01596 03723 04681

01170 06915 01915

00426 04574 05000

00851 03830 05319

00532 04681 04787

00426 04149 05425

00426 04574 05000

00213 05638 04149

]]]]]]]]]]]]]]]]]]]]]]]]]]

]

1198773=

[[[[[[[[[[[[

[

01170 04787 04043

02021 04149 03830

00638 04575 04787

00532 04255 05213

00851 07447 01702

00638 07766 01596

00851 08404 00745

00958 07340 01702

00532 03191 06277

]]]]]]]]]]]]

]

1198774= [

01702 04468 03830

00106 05213 04681]

1198775=

[[[[[[[

[

02447 05638 01915

00957 05000 04043

02340 04787 02872

01064 04894 04042

00957 04681 04362

00638 05532 03830

]]]]]]]

]

(4)

46 Step 6 Make Fuzzy Composition Synthesize the first-level fuzzy relation matrix R with the local weight 119882

119871 and

then the membership matrix 119861119894could be obtained which is

call the first-level fuzzy comprehensive evaluation matrix

119861119894= 119882119871o119877 = (119887

1198941 1198871198942 119887

119894119898) (5)

Due to the hierarchical structure of the evaluation indexsystem the second-level fuzzy relation matrix 119877

1015840 needs to becalculated

1198771015840=

[[[[

[

1198611

1198612

119861119896

]]]]

]

=[[[

[

11988711

11988712

sdot sdot sdot 1198871119898

11988721

11988722

sdot sdot sdot 1198872119898

sdot sdot sdot sdot sdot sdot sdot sdot sdot sdot sdot sdot

1198871198961

1198871198962

sdot sdot sdot 119887119896119898

]]]

]

(6)

Then combined with the weight matrix 119882 the second-level fuzzy comprehensive evaluation matrix B can be calcu-lated as follows

B = 119882o1198771015840 = (1198871 1198872 119887

119898) (7)

where 119887119898is the membership degree of the 119898th remark in

remark set VIn this paper the first-level fuzzy comprehensive evalua-

tion matrix 119861119894is calculated as follows

1198611= 1198821198711o1198771

= (020 007 037 008 022 006)

o

[[[[[[[

[

01277 04574 04149

04255 03830 05745

02660 05745 01595

00426 05638 03936

01702 03192 05106

00213 03617 06170

]]]]]]]

]

= (01690 04679 03631)

(8)

Similarly we can obtain

1198612= (01005 04585 04310)

1198613= (01073 05905 03022)

1198614= (01128 04736 04136)

1198615= (01710 05133 03157)

(9)

Then we obtain the second-level fuzzy relationmatrix1198771015840

1198771015840=

[[[[[

[

01690 04679 03631

01005 04585 04310

01073 05905 03022

01128 04736 04136

01710 05133 03157

]]]]]

]

(10)

The second-level fuzzy comprehensive evaluation matrixB can be calculated as follows

B = 119882o1198771015840

= (020 022 015 012 031)

o[[[[[

[

01690 04679 03631

01005 04585 04310

01073 05905 03022

01128 04736 04136

01710 05133 03157

]]]]]

]

= (01385 04990 03603)

(11)

47 Step 7 Rate and Conclude the Grade Level Accordingto the maximum membership degree principle when 119887

1198940=

max 119887119894(1 le 119894 le 119898) we can judge that the evaluated object

belongs to the 1198940grade

In this paper since 1198872

= max 119887119894(1 le 119894 le 3) =

04990 it is shown that the risk grade of ldquoZhejiang-FuzhourdquoUHV power transmission construction project belongs toldquomoderaterdquo which means the occurrence probability of thisproject risk is medium and the risk occurrence will causegeneral loss So it is necessary for the project managers to

Mathematical Problems in Engineering 11

Table 8 Judgment matrixes and weights of ldquosociety riskrdquo criteria

Society risk 11986234

11986235

11986236

11986237

11986238

11986239

Local weight11986234

1 23 12 18 2 3 02911986235

043 1 05 08 09 13 01211986236

083 2 1 15 17 25 02411986237

056 125 067 1 11 17 01611986238

05 011 059 091 1 15 01011986239

033 077 04 059 067 1 009120582max = 59109 CI = minus00178 CR = minus00141 lt 01

Table 9 The value of RI

119899 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15RI 0 052 089 112 126 136 141 145 149 152 154 156 157 158

carry out some specific risk control measures to make theconstruction of this project run successfully

At the meantime valuing the evaluation result of indi-cators in criteria layer in centesimal form can help projectmanagers to analyze the project riskmore efficiently Supposethe comment set V = [V

1 V2 V3] = 90 50 10 and then

the centesimal value of each indicator in criteria layer can becalculated as follows

1198801= 01690 times 90 + 04679 times 50 + 03631 times 10

= 422383

1198802= 01005 times 90 + 04585 times 50 + 04310 times 10

= 362830

1198803= 01073 times 90 + 05905 times 50 + 03022 times 10

= 422

1198804= 01128 times 90 + 04736 times 50 + 04136 times 10

= 379660

1198805= 01710 times 90 + 05133 times 50 + 03157 times 10

= 442085

(12)

The centesimal value (119880) of risk evaluation of ldquoZhejiang-Fuzhourdquo UHV power transmission construction project canbe calculated as

119880 = 01385 times 90 + 04990 times 50 + 03603 times 10

= 410205

(13)

Figure 8 compares the centesimal value of each indicatorin criteria layer and we can see

1198805≻ 1198801≻ 1198803≻ 119880 ≻ 119880

4≻ 1198802 (14)

Therefore the centesimal value of ldquosociety riskrdquo is thehighest followed by ldquopolicy and law riskrdquo ldquotechnology riskrdquoldquonatural environmental riskrdquo and ldquomanagement riskrdquo Thecentesimal values of both ldquomanagement riskrdquo and ldquonatural

422383

36283

422

37966

442085

Policy and law

Management

Technology

Natural environmental

Society

Centesimal value

Centesimal value of U

risk

risk

risk

risk

risk0 5 10 15 20 25 30 35 40 45 50

Figure 8 Centesimal value of each indicator in criteria layer

environmental riskrdquo are lower than that of the project119880 whilethe centesimal values of other three indicators are larger thanthat of the project 119880 The criteria ldquoSociety riskrdquo ldquopolicy andlaw riskrdquo and ldquotechnology riskrdquo should be paidmore attentionin the risk management and control for ldquoZhejiang-FuzhourdquoUHV power transmission construction project

5 Risk Control Recommendations

According to the risk evaluation result we should paymore attention to ldquosociety riskrdquo ldquopolicy and law riskrdquo andldquotechnology riskrdquoThe specific risk control recommendationsare as follows

51 Risk Control Recommendations for ldquoSociety Riskrdquo

(1) Before and during the construction of ldquoZhejiang-Fuzhourdquo UHV power transmission project the pro-paganda work should be done in the form of TVradio newspapers brochures and so on The con-struction significance and engineering safety knowl-edge related to this project should be propagandizedin order to eliminate the worries from society fol-lowers and local villagers about this UHV powertransmission project

12 Mathematical Problems in Engineering

Table 10 The weight of risk indicators

Criteria layer Index layerIndicator Weight (119882) Indicator Local weight (119882

119871) Global weight (119882

119866)

Policy and law risk (1198801) 020

1198621

020 004001198622

007 001401198623

037 007401198624

008 001601198625

022 004401198626

006 00120

Management risk (1198802) 022

1198627

003 000661198628

007 001541198629

009 0019811986210

006 0013211986211

004 0008811986212

011 0024211986213

009 0019811986214

006 0013211986215

012 0026411986216

009 0019811986217

003 0006611986218

005 0011011986219

004 0008811986220

004 0008811986221

004 0008811986222

003 00066

Technology risk (1198803) 015

11986223

014 0021011986224

020 0030011986225

007 0010511986226

006 0009011986227

011 0016511986228

009 0013511986229

013 0019511986230

014 0021011986231

006 00090

Natural environment risk (1198804) 012 119862

32064 00768

11986233

036 00432

Society risk (1198805) 031

11986234

029 0089911986235

012 0037211986236

024 0074411986237

016 0049611986238

01 0031011986239

009 00279

(2) Grid company should try to sign a contract withlocal government which strives to make the localgovernment be responsible for land requisition houserelocation and crop compensation Grid companycan also set up aworking group to coordinate with thelocal government The determination of land com-pensation standards not only abides by the relevantlaws and regulations but also takes the opinions oflocal masses into consideration

(3) The terrain and ecological resources along the projectline should be fully understood when selecting theoptimal route Having some experienced practition-ers on the team and considering the local customsare better for the route determination During theproject construction the water and soil loss as wellas deforestation should be reduced as far as possibleWhen the project is finished the vegetation should berestored timely

Mathematical Problems in Engineering 13

(4) Keep close touch with the local government andpublic security organization in order to strengthen thesecurity of project construction the ldquomass incidentsrdquosuch as petitions demagoguism and demonstrationshould be paid close attention and some relatedmeasures such as propaganda and negotiation shouldbe taken timely strengthen the project constructionmanagement and perform civilized construction andreduce the negative impacts on local residents to aminimum

52 Risk Control Recommendations for ldquoPolicy and Law Riskrdquo

(1) The project-related personnel especially the projectmanagers should carefully study the policies andlaws related to land management deforestation loanand environmental protection and the related legalcounsel should be engaged in order to reduce the legalrisk during the project construction

(2) Strengthen the research on the policies and guidancedocuments related to energy development and plan-ning

(3) Strengthen the communication with the governmentdepartment to improve the efficiency of project exam-ination and approval

(4) Because the size and weight of UHV equipment arebigger and heavier the traffic laws and regulationsshould be carefully studied to avoid the conflictrelated to UHV equipment transportation Trans-portation limitations should be taken into considera-tion when selecting the UHV equipment and surveyon the transport route is very necessary

53 Risk Control Recommendations for ldquoTechnology Riskrdquo

(1) Track the meteorological information timely andarrange the construction plan according to theweather condition some necessary measures shouldbe taken to protect the equipment from rainwatersuch as building the temporary drain and increasingthe pumping equipment

(2) The earth-rock excavation should keep a reasonableproportion based on the quantity calculation

(3) For waterway transport due to the constant changeof shipping lane the simulation navigation shouldbe performed six months in advance to ensure thetransportation safety

(4) Measure the earth resistivity and design the ground-ing grid establish special subjects to study the impactsof ground resistance on UHVGIS equipment and theoperation of control and protection system

(5) Design the crossing construction based on differ-ent crossing facilities to reduce the risk and diffi-culty when crossing the electricity lines the crossingscheme should be designed at the design stage and

take the terrain characteristic along the project lineinto consideration

(6) The material transport plan should take weather andtransportation environment into consideration opti-mize the use of different transportation facilities andmake the fullest use of crawler-transporter vehicleand cableway

6 Conclusions

In this paper a hybrid evaluation model based on AHPand FCE method is implemented to evaluate the risk ofldquoZhejiang-Fuzhourdquo UHV power transmission constructionprojectThis hybrid evaluationmodel takes full advantages ofAHP and FCEmethod After the risk evaluation index systemis built the AHP is used to determine the index weightand FCE method is used to evaluate the project risk Finallythe specific risk control recommendations are proposed Themain results of risk evaluation of ldquoZhejiang-Fuzhourdquo UHVpower transmission construction project are as follows

(1) The risk grade of ldquoZhejiang-Fuzhourdquo UHV powertransmission construction project belongs to ldquomod-eraterdquo which indicates the occurrence probability ofproject risk is medium and the risk occurrence willcause general loss

(2) ldquoSociety riskrdquo has the highest level and the next isldquopolicy and law riskrdquo ldquotechnique riskrdquo ldquonatural envi-ronmental riskrdquo and ldquomanagement riskrdquo respectivelyldquosociety riskrdquo ldquopolicy and law riskrdquo and ldquotechnologyriskrdquo should be paid more attention in the risk man-agement and control for ldquoZhejiang-Fuzhourdquo UHVpower transmission construction project

(3) Risk control recommendations for main risk criteriawhich include society risk policy and law risk andtechnology risk are proposed

(4) This hybrid evaluation model is feasible and effectivewhich can effectively evaluate the risk of UHV powertransmission construction project

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

This study is supported by the Humanity and Social Scienceproject of the Ministry of Education of China (Project no11YJA790217) and the National Natural Science Foundationof China (Project no 71373076)

References

[1] J P Liu D X Niu and X H Song ldquoThe energy supply anddemand pattern of China a review of evolution and sustainabledevelopmentrdquo Renewable and Sustainable Energy Reviews vol25 pp 220ndash228 2013

14 Mathematical Problems in Engineering

[2] C C Lin C H Yang and J Z Shyua ldquoA comparison ofinnovation policy in the smart grid industry across the pacificchina and the USArdquo Energy Policy vol 57 pp 119ndash132 2013

[3] M Bolinger and R Wiser ldquoA comparative analysis of businessstructures suitable for farmer-ownedwind power projects in theUnited Statesrdquo Energy Policy vol 34 no 14 pp 1750ndash1761 2006

[4] S Grassi N Chokani and R S Abhari ldquoLarge scale technicaland economical assessment of wind energy potential with a GIStool case study Iowardquo Energy Policy vol 45 pp 73ndash85 2012

[5] MHellstrom I Ruuska KWikstrom andD Jafs ldquoProject gov-ernance and path creation in the early stages of Finnish nuclearpower projectsrdquo International Journal of Project Managementvol 31 no 5 pp 712ndash723 2013

[6] P Baumann and G Stevanella ldquoFish passage principles to beconsidered for medium and large dams the case study of afish passage concept for a hydroelectric power project on theMekong mainstem in Laosrdquo Ecological Engineering vol 48 pp79ndash85 2012

[7] W Amatayakul and G Berndes ldquoDetermining factor for thedevelopment of CDM biomass power projectsrdquo Energy forSustainable Development vol 16 pp 197ndash203 2012

[8] J L Liu Q X Li and Y H Wang ldquoRisk analysis in ultradeep scientific drilling project-A fuzzy synthetic evaluationapproachrdquo International Journal of Project Management vol 31no 3 pp 449ndash458 2013

[9] A Badri S Nadeau and A Gbodossou ldquoA new practicalapproach to risk management for underground mining projectin Quebecrdquo Journal of Loss Prevention in the Process Industriesvol 26 no 6 pp 1145ndash1158 2013

[10] J B Song D R Song X Q Zhang and Y Sun ldquoRiskidentification for PPP waste-to-energy incineration projects inChinardquo Energy Policy vol 61 pp 953ndash962 2013

[11] Y Hu J F Du X Z Zhang et al ldquoAn integrative frameworkfor intelligent software project risk planningrdquo Decision SupportSystems vol 55 no 4 pp 927ndash937 2013

[12] T L Saaty The Analytic Hierarchy Process McGraw-Hill NewYork NY USA 1980

[13] M P Amiri ldquoProject selection for oil-fields development byusing the AHP and fuzzy TOPSIS methodsrdquo Expert Systemswith Applications vol 37 no 9 pp 6218ndash6224 2010

[14] H Z Li and S Guo ldquoExternal economies evaluation of windpower engineering project based on analytic hierarchy processand matter-element extension modelrdquo Mathematical Problemsin Engineering vol 2013 Article ID 848901 11 pages 2013

[15] F-G Chen H-L Yao andW-G Shi ldquoApplication of fuzzy andsynthetic judgment to risk assessment of dammed lakerdquo Journalof Shanghai Jiaotong University vol 45 no 1 pp 67ndash75 2011

[16] K Fang B-F He M Yang and Z-C Wang ldquoApplication offuzzy comprehensive evaluation method to CENSrdquo Journal ofHarbin Institute of Technology vol 43 no 5 pp 30ndash36 2011

Submit your manuscripts athttpwwwhindawicom

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mathematical Problems in Engineering

Hindawi Publishing Corporationhttpwwwhindawicom

Differential EquationsInternational Journal of

Volume 2014

Applied MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mathematical PhysicsAdvances in

Complex AnalysisJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

OptimizationJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Operations ResearchAdvances in

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Function Spaces

Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of Mathematics and Mathematical Sciences

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Algebra

Discrete Dynamics in Nature and Society

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Decision SciencesAdvances in

Discrete MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom

Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Stochastic AnalysisInternational Journal of

Mathematical Problems in Engineering 11

Table 8 Judgment matrixes and weights of ldquosociety riskrdquo criteria

Society risk 11986234

11986235

11986236

11986237

11986238

11986239

Local weight11986234

1 23 12 18 2 3 02911986235

043 1 05 08 09 13 01211986236

083 2 1 15 17 25 02411986237

056 125 067 1 11 17 01611986238

05 011 059 091 1 15 01011986239

033 077 04 059 067 1 009120582max = 59109 CI = minus00178 CR = minus00141 lt 01

Table 9 The value of RI

119899 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15RI 0 052 089 112 126 136 141 145 149 152 154 156 157 158

carry out some specific risk control measures to make theconstruction of this project run successfully

At the meantime valuing the evaluation result of indi-cators in criteria layer in centesimal form can help projectmanagers to analyze the project riskmore efficiently Supposethe comment set V = [V

1 V2 V3] = 90 50 10 and then

the centesimal value of each indicator in criteria layer can becalculated as follows

1198801= 01690 times 90 + 04679 times 50 + 03631 times 10

= 422383

1198802= 01005 times 90 + 04585 times 50 + 04310 times 10

= 362830

1198803= 01073 times 90 + 05905 times 50 + 03022 times 10

= 422

1198804= 01128 times 90 + 04736 times 50 + 04136 times 10

= 379660

1198805= 01710 times 90 + 05133 times 50 + 03157 times 10

= 442085

(12)

The centesimal value (119880) of risk evaluation of ldquoZhejiang-Fuzhourdquo UHV power transmission construction project canbe calculated as

119880 = 01385 times 90 + 04990 times 50 + 03603 times 10

= 410205

(13)

Figure 8 compares the centesimal value of each indicatorin criteria layer and we can see

1198805≻ 1198801≻ 1198803≻ 119880 ≻ 119880

4≻ 1198802 (14)

Therefore the centesimal value of ldquosociety riskrdquo is thehighest followed by ldquopolicy and law riskrdquo ldquotechnology riskrdquoldquonatural environmental riskrdquo and ldquomanagement riskrdquo Thecentesimal values of both ldquomanagement riskrdquo and ldquonatural

422383

36283

422

37966

442085

Policy and law

Management

Technology

Natural environmental

Society

Centesimal value

Centesimal value of U

risk

risk

risk

risk

risk0 5 10 15 20 25 30 35 40 45 50

Figure 8 Centesimal value of each indicator in criteria layer

environmental riskrdquo are lower than that of the project119880 whilethe centesimal values of other three indicators are larger thanthat of the project 119880 The criteria ldquoSociety riskrdquo ldquopolicy andlaw riskrdquo and ldquotechnology riskrdquo should be paidmore attentionin the risk management and control for ldquoZhejiang-FuzhourdquoUHV power transmission construction project

5 Risk Control Recommendations

According to the risk evaluation result we should paymore attention to ldquosociety riskrdquo ldquopolicy and law riskrdquo andldquotechnology riskrdquoThe specific risk control recommendationsare as follows

51 Risk Control Recommendations for ldquoSociety Riskrdquo

(1) Before and during the construction of ldquoZhejiang-Fuzhourdquo UHV power transmission project the pro-paganda work should be done in the form of TVradio newspapers brochures and so on The con-struction significance and engineering safety knowl-edge related to this project should be propagandizedin order to eliminate the worries from society fol-lowers and local villagers about this UHV powertransmission project

12 Mathematical Problems in Engineering

Table 10 The weight of risk indicators

Criteria layer Index layerIndicator Weight (119882) Indicator Local weight (119882

119871) Global weight (119882

119866)

Policy and law risk (1198801) 020

1198621

020 004001198622

007 001401198623

037 007401198624

008 001601198625

022 004401198626

006 00120

Management risk (1198802) 022

1198627

003 000661198628

007 001541198629

009 0019811986210

006 0013211986211

004 0008811986212

011 0024211986213

009 0019811986214

006 0013211986215

012 0026411986216

009 0019811986217

003 0006611986218

005 0011011986219

004 0008811986220

004 0008811986221

004 0008811986222

003 00066

Technology risk (1198803) 015

11986223

014 0021011986224

020 0030011986225

007 0010511986226

006 0009011986227

011 0016511986228

009 0013511986229

013 0019511986230

014 0021011986231

006 00090

Natural environment risk (1198804) 012 119862

32064 00768

11986233

036 00432

Society risk (1198805) 031

11986234

029 0089911986235

012 0037211986236

024 0074411986237

016 0049611986238

01 0031011986239

009 00279

(2) Grid company should try to sign a contract withlocal government which strives to make the localgovernment be responsible for land requisition houserelocation and crop compensation Grid companycan also set up aworking group to coordinate with thelocal government The determination of land com-pensation standards not only abides by the relevantlaws and regulations but also takes the opinions oflocal masses into consideration

(3) The terrain and ecological resources along the projectline should be fully understood when selecting theoptimal route Having some experienced practition-ers on the team and considering the local customsare better for the route determination During theproject construction the water and soil loss as wellas deforestation should be reduced as far as possibleWhen the project is finished the vegetation should berestored timely

Mathematical Problems in Engineering 13

(4) Keep close touch with the local government andpublic security organization in order to strengthen thesecurity of project construction the ldquomass incidentsrdquosuch as petitions demagoguism and demonstrationshould be paid close attention and some relatedmeasures such as propaganda and negotiation shouldbe taken timely strengthen the project constructionmanagement and perform civilized construction andreduce the negative impacts on local residents to aminimum

52 Risk Control Recommendations for ldquoPolicy and Law Riskrdquo

(1) The project-related personnel especially the projectmanagers should carefully study the policies andlaws related to land management deforestation loanand environmental protection and the related legalcounsel should be engaged in order to reduce the legalrisk during the project construction

(2) Strengthen the research on the policies and guidancedocuments related to energy development and plan-ning

(3) Strengthen the communication with the governmentdepartment to improve the efficiency of project exam-ination and approval

(4) Because the size and weight of UHV equipment arebigger and heavier the traffic laws and regulationsshould be carefully studied to avoid the conflictrelated to UHV equipment transportation Trans-portation limitations should be taken into considera-tion when selecting the UHV equipment and surveyon the transport route is very necessary

53 Risk Control Recommendations for ldquoTechnology Riskrdquo

(1) Track the meteorological information timely andarrange the construction plan according to theweather condition some necessary measures shouldbe taken to protect the equipment from rainwatersuch as building the temporary drain and increasingthe pumping equipment

(2) The earth-rock excavation should keep a reasonableproportion based on the quantity calculation

(3) For waterway transport due to the constant changeof shipping lane the simulation navigation shouldbe performed six months in advance to ensure thetransportation safety

(4) Measure the earth resistivity and design the ground-ing grid establish special subjects to study the impactsof ground resistance on UHVGIS equipment and theoperation of control and protection system

(5) Design the crossing construction based on differ-ent crossing facilities to reduce the risk and diffi-culty when crossing the electricity lines the crossingscheme should be designed at the design stage and

take the terrain characteristic along the project lineinto consideration

(6) The material transport plan should take weather andtransportation environment into consideration opti-mize the use of different transportation facilities andmake the fullest use of crawler-transporter vehicleand cableway

6 Conclusions

In this paper a hybrid evaluation model based on AHPand FCE method is implemented to evaluate the risk ofldquoZhejiang-Fuzhourdquo UHV power transmission constructionprojectThis hybrid evaluationmodel takes full advantages ofAHP and FCEmethod After the risk evaluation index systemis built the AHP is used to determine the index weightand FCE method is used to evaluate the project risk Finallythe specific risk control recommendations are proposed Themain results of risk evaluation of ldquoZhejiang-Fuzhourdquo UHVpower transmission construction project are as follows

(1) The risk grade of ldquoZhejiang-Fuzhourdquo UHV powertransmission construction project belongs to ldquomod-eraterdquo which indicates the occurrence probability ofproject risk is medium and the risk occurrence willcause general loss

(2) ldquoSociety riskrdquo has the highest level and the next isldquopolicy and law riskrdquo ldquotechnique riskrdquo ldquonatural envi-ronmental riskrdquo and ldquomanagement riskrdquo respectivelyldquosociety riskrdquo ldquopolicy and law riskrdquo and ldquotechnologyriskrdquo should be paid more attention in the risk man-agement and control for ldquoZhejiang-Fuzhourdquo UHVpower transmission construction project

(3) Risk control recommendations for main risk criteriawhich include society risk policy and law risk andtechnology risk are proposed

(4) This hybrid evaluation model is feasible and effectivewhich can effectively evaluate the risk of UHV powertransmission construction project

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

This study is supported by the Humanity and Social Scienceproject of the Ministry of Education of China (Project no11YJA790217) and the National Natural Science Foundationof China (Project no 71373076)

References

[1] J P Liu D X Niu and X H Song ldquoThe energy supply anddemand pattern of China a review of evolution and sustainabledevelopmentrdquo Renewable and Sustainable Energy Reviews vol25 pp 220ndash228 2013

14 Mathematical Problems in Engineering

[2] C C Lin C H Yang and J Z Shyua ldquoA comparison ofinnovation policy in the smart grid industry across the pacificchina and the USArdquo Energy Policy vol 57 pp 119ndash132 2013

[3] M Bolinger and R Wiser ldquoA comparative analysis of businessstructures suitable for farmer-ownedwind power projects in theUnited Statesrdquo Energy Policy vol 34 no 14 pp 1750ndash1761 2006

[4] S Grassi N Chokani and R S Abhari ldquoLarge scale technicaland economical assessment of wind energy potential with a GIStool case study Iowardquo Energy Policy vol 45 pp 73ndash85 2012

[5] MHellstrom I Ruuska KWikstrom andD Jafs ldquoProject gov-ernance and path creation in the early stages of Finnish nuclearpower projectsrdquo International Journal of Project Managementvol 31 no 5 pp 712ndash723 2013

[6] P Baumann and G Stevanella ldquoFish passage principles to beconsidered for medium and large dams the case study of afish passage concept for a hydroelectric power project on theMekong mainstem in Laosrdquo Ecological Engineering vol 48 pp79ndash85 2012

[7] W Amatayakul and G Berndes ldquoDetermining factor for thedevelopment of CDM biomass power projectsrdquo Energy forSustainable Development vol 16 pp 197ndash203 2012

[8] J L Liu Q X Li and Y H Wang ldquoRisk analysis in ultradeep scientific drilling project-A fuzzy synthetic evaluationapproachrdquo International Journal of Project Management vol 31no 3 pp 449ndash458 2013

[9] A Badri S Nadeau and A Gbodossou ldquoA new practicalapproach to risk management for underground mining projectin Quebecrdquo Journal of Loss Prevention in the Process Industriesvol 26 no 6 pp 1145ndash1158 2013

[10] J B Song D R Song X Q Zhang and Y Sun ldquoRiskidentification for PPP waste-to-energy incineration projects inChinardquo Energy Policy vol 61 pp 953ndash962 2013

[11] Y Hu J F Du X Z Zhang et al ldquoAn integrative frameworkfor intelligent software project risk planningrdquo Decision SupportSystems vol 55 no 4 pp 927ndash937 2013

[12] T L Saaty The Analytic Hierarchy Process McGraw-Hill NewYork NY USA 1980

[13] M P Amiri ldquoProject selection for oil-fields development byusing the AHP and fuzzy TOPSIS methodsrdquo Expert Systemswith Applications vol 37 no 9 pp 6218ndash6224 2010

[14] H Z Li and S Guo ldquoExternal economies evaluation of windpower engineering project based on analytic hierarchy processand matter-element extension modelrdquo Mathematical Problemsin Engineering vol 2013 Article ID 848901 11 pages 2013

[15] F-G Chen H-L Yao andW-G Shi ldquoApplication of fuzzy andsynthetic judgment to risk assessment of dammed lakerdquo Journalof Shanghai Jiaotong University vol 45 no 1 pp 67ndash75 2011

[16] K Fang B-F He M Yang and Z-C Wang ldquoApplication offuzzy comprehensive evaluation method to CENSrdquo Journal ofHarbin Institute of Technology vol 43 no 5 pp 30ndash36 2011

Submit your manuscripts athttpwwwhindawicom

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mathematical Problems in Engineering

Hindawi Publishing Corporationhttpwwwhindawicom

Differential EquationsInternational Journal of

Volume 2014

Applied MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mathematical PhysicsAdvances in

Complex AnalysisJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

OptimizationJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Operations ResearchAdvances in

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Function Spaces

Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of Mathematics and Mathematical Sciences

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Algebra

Discrete Dynamics in Nature and Society

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Decision SciencesAdvances in

Discrete MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom

Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Stochastic AnalysisInternational Journal of

12 Mathematical Problems in Engineering

Table 10 The weight of risk indicators

Criteria layer Index layerIndicator Weight (119882) Indicator Local weight (119882

119871) Global weight (119882

119866)

Policy and law risk (1198801) 020

1198621

020 004001198622

007 001401198623

037 007401198624

008 001601198625

022 004401198626

006 00120

Management risk (1198802) 022

1198627

003 000661198628

007 001541198629

009 0019811986210

006 0013211986211

004 0008811986212

011 0024211986213

009 0019811986214

006 0013211986215

012 0026411986216

009 0019811986217

003 0006611986218

005 0011011986219

004 0008811986220

004 0008811986221

004 0008811986222

003 00066

Technology risk (1198803) 015

11986223

014 0021011986224

020 0030011986225

007 0010511986226

006 0009011986227

011 0016511986228

009 0013511986229

013 0019511986230

014 0021011986231

006 00090

Natural environment risk (1198804) 012 119862

32064 00768

11986233

036 00432

Society risk (1198805) 031

11986234

029 0089911986235

012 0037211986236

024 0074411986237

016 0049611986238

01 0031011986239

009 00279

(2) Grid company should try to sign a contract withlocal government which strives to make the localgovernment be responsible for land requisition houserelocation and crop compensation Grid companycan also set up aworking group to coordinate with thelocal government The determination of land com-pensation standards not only abides by the relevantlaws and regulations but also takes the opinions oflocal masses into consideration

(3) The terrain and ecological resources along the projectline should be fully understood when selecting theoptimal route Having some experienced practition-ers on the team and considering the local customsare better for the route determination During theproject construction the water and soil loss as wellas deforestation should be reduced as far as possibleWhen the project is finished the vegetation should berestored timely

Mathematical Problems in Engineering 13

(4) Keep close touch with the local government andpublic security organization in order to strengthen thesecurity of project construction the ldquomass incidentsrdquosuch as petitions demagoguism and demonstrationshould be paid close attention and some relatedmeasures such as propaganda and negotiation shouldbe taken timely strengthen the project constructionmanagement and perform civilized construction andreduce the negative impacts on local residents to aminimum

52 Risk Control Recommendations for ldquoPolicy and Law Riskrdquo

(1) The project-related personnel especially the projectmanagers should carefully study the policies andlaws related to land management deforestation loanand environmental protection and the related legalcounsel should be engaged in order to reduce the legalrisk during the project construction

(2) Strengthen the research on the policies and guidancedocuments related to energy development and plan-ning

(3) Strengthen the communication with the governmentdepartment to improve the efficiency of project exam-ination and approval

(4) Because the size and weight of UHV equipment arebigger and heavier the traffic laws and regulationsshould be carefully studied to avoid the conflictrelated to UHV equipment transportation Trans-portation limitations should be taken into considera-tion when selecting the UHV equipment and surveyon the transport route is very necessary

53 Risk Control Recommendations for ldquoTechnology Riskrdquo

(1) Track the meteorological information timely andarrange the construction plan according to theweather condition some necessary measures shouldbe taken to protect the equipment from rainwatersuch as building the temporary drain and increasingthe pumping equipment

(2) The earth-rock excavation should keep a reasonableproportion based on the quantity calculation

(3) For waterway transport due to the constant changeof shipping lane the simulation navigation shouldbe performed six months in advance to ensure thetransportation safety

(4) Measure the earth resistivity and design the ground-ing grid establish special subjects to study the impactsof ground resistance on UHVGIS equipment and theoperation of control and protection system

(5) Design the crossing construction based on differ-ent crossing facilities to reduce the risk and diffi-culty when crossing the electricity lines the crossingscheme should be designed at the design stage and

take the terrain characteristic along the project lineinto consideration

(6) The material transport plan should take weather andtransportation environment into consideration opti-mize the use of different transportation facilities andmake the fullest use of crawler-transporter vehicleand cableway

6 Conclusions

In this paper a hybrid evaluation model based on AHPand FCE method is implemented to evaluate the risk ofldquoZhejiang-Fuzhourdquo UHV power transmission constructionprojectThis hybrid evaluationmodel takes full advantages ofAHP and FCEmethod After the risk evaluation index systemis built the AHP is used to determine the index weightand FCE method is used to evaluate the project risk Finallythe specific risk control recommendations are proposed Themain results of risk evaluation of ldquoZhejiang-Fuzhourdquo UHVpower transmission construction project are as follows

(1) The risk grade of ldquoZhejiang-Fuzhourdquo UHV powertransmission construction project belongs to ldquomod-eraterdquo which indicates the occurrence probability ofproject risk is medium and the risk occurrence willcause general loss

(2) ldquoSociety riskrdquo has the highest level and the next isldquopolicy and law riskrdquo ldquotechnique riskrdquo ldquonatural envi-ronmental riskrdquo and ldquomanagement riskrdquo respectivelyldquosociety riskrdquo ldquopolicy and law riskrdquo and ldquotechnologyriskrdquo should be paid more attention in the risk man-agement and control for ldquoZhejiang-Fuzhourdquo UHVpower transmission construction project

(3) Risk control recommendations for main risk criteriawhich include society risk policy and law risk andtechnology risk are proposed

(4) This hybrid evaluation model is feasible and effectivewhich can effectively evaluate the risk of UHV powertransmission construction project

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

This study is supported by the Humanity and Social Scienceproject of the Ministry of Education of China (Project no11YJA790217) and the National Natural Science Foundationof China (Project no 71373076)

References

[1] J P Liu D X Niu and X H Song ldquoThe energy supply anddemand pattern of China a review of evolution and sustainabledevelopmentrdquo Renewable and Sustainable Energy Reviews vol25 pp 220ndash228 2013

14 Mathematical Problems in Engineering

[2] C C Lin C H Yang and J Z Shyua ldquoA comparison ofinnovation policy in the smart grid industry across the pacificchina and the USArdquo Energy Policy vol 57 pp 119ndash132 2013

[3] M Bolinger and R Wiser ldquoA comparative analysis of businessstructures suitable for farmer-ownedwind power projects in theUnited Statesrdquo Energy Policy vol 34 no 14 pp 1750ndash1761 2006

[4] S Grassi N Chokani and R S Abhari ldquoLarge scale technicaland economical assessment of wind energy potential with a GIStool case study Iowardquo Energy Policy vol 45 pp 73ndash85 2012

[5] MHellstrom I Ruuska KWikstrom andD Jafs ldquoProject gov-ernance and path creation in the early stages of Finnish nuclearpower projectsrdquo International Journal of Project Managementvol 31 no 5 pp 712ndash723 2013

[6] P Baumann and G Stevanella ldquoFish passage principles to beconsidered for medium and large dams the case study of afish passage concept for a hydroelectric power project on theMekong mainstem in Laosrdquo Ecological Engineering vol 48 pp79ndash85 2012

[7] W Amatayakul and G Berndes ldquoDetermining factor for thedevelopment of CDM biomass power projectsrdquo Energy forSustainable Development vol 16 pp 197ndash203 2012

[8] J L Liu Q X Li and Y H Wang ldquoRisk analysis in ultradeep scientific drilling project-A fuzzy synthetic evaluationapproachrdquo International Journal of Project Management vol 31no 3 pp 449ndash458 2013

[9] A Badri S Nadeau and A Gbodossou ldquoA new practicalapproach to risk management for underground mining projectin Quebecrdquo Journal of Loss Prevention in the Process Industriesvol 26 no 6 pp 1145ndash1158 2013

[10] J B Song D R Song X Q Zhang and Y Sun ldquoRiskidentification for PPP waste-to-energy incineration projects inChinardquo Energy Policy vol 61 pp 953ndash962 2013

[11] Y Hu J F Du X Z Zhang et al ldquoAn integrative frameworkfor intelligent software project risk planningrdquo Decision SupportSystems vol 55 no 4 pp 927ndash937 2013

[12] T L Saaty The Analytic Hierarchy Process McGraw-Hill NewYork NY USA 1980

[13] M P Amiri ldquoProject selection for oil-fields development byusing the AHP and fuzzy TOPSIS methodsrdquo Expert Systemswith Applications vol 37 no 9 pp 6218ndash6224 2010

[14] H Z Li and S Guo ldquoExternal economies evaluation of windpower engineering project based on analytic hierarchy processand matter-element extension modelrdquo Mathematical Problemsin Engineering vol 2013 Article ID 848901 11 pages 2013

[15] F-G Chen H-L Yao andW-G Shi ldquoApplication of fuzzy andsynthetic judgment to risk assessment of dammed lakerdquo Journalof Shanghai Jiaotong University vol 45 no 1 pp 67ndash75 2011

[16] K Fang B-F He M Yang and Z-C Wang ldquoApplication offuzzy comprehensive evaluation method to CENSrdquo Journal ofHarbin Institute of Technology vol 43 no 5 pp 30ndash36 2011

Submit your manuscripts athttpwwwhindawicom

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mathematical Problems in Engineering

Hindawi Publishing Corporationhttpwwwhindawicom

Differential EquationsInternational Journal of

Volume 2014

Applied MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mathematical PhysicsAdvances in

Complex AnalysisJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

OptimizationJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Operations ResearchAdvances in

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Function Spaces

Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of Mathematics and Mathematical Sciences

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Algebra

Discrete Dynamics in Nature and Society

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Decision SciencesAdvances in

Discrete MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom

Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Stochastic AnalysisInternational Journal of

Mathematical Problems in Engineering 13

(4) Keep close touch with the local government andpublic security organization in order to strengthen thesecurity of project construction the ldquomass incidentsrdquosuch as petitions demagoguism and demonstrationshould be paid close attention and some relatedmeasures such as propaganda and negotiation shouldbe taken timely strengthen the project constructionmanagement and perform civilized construction andreduce the negative impacts on local residents to aminimum

52 Risk Control Recommendations for ldquoPolicy and Law Riskrdquo

(1) The project-related personnel especially the projectmanagers should carefully study the policies andlaws related to land management deforestation loanand environmental protection and the related legalcounsel should be engaged in order to reduce the legalrisk during the project construction

(2) Strengthen the research on the policies and guidancedocuments related to energy development and plan-ning

(3) Strengthen the communication with the governmentdepartment to improve the efficiency of project exam-ination and approval

(4) Because the size and weight of UHV equipment arebigger and heavier the traffic laws and regulationsshould be carefully studied to avoid the conflictrelated to UHV equipment transportation Trans-portation limitations should be taken into considera-tion when selecting the UHV equipment and surveyon the transport route is very necessary

53 Risk Control Recommendations for ldquoTechnology Riskrdquo

(1) Track the meteorological information timely andarrange the construction plan according to theweather condition some necessary measures shouldbe taken to protect the equipment from rainwatersuch as building the temporary drain and increasingthe pumping equipment

(2) The earth-rock excavation should keep a reasonableproportion based on the quantity calculation

(3) For waterway transport due to the constant changeof shipping lane the simulation navigation shouldbe performed six months in advance to ensure thetransportation safety

(4) Measure the earth resistivity and design the ground-ing grid establish special subjects to study the impactsof ground resistance on UHVGIS equipment and theoperation of control and protection system

(5) Design the crossing construction based on differ-ent crossing facilities to reduce the risk and diffi-culty when crossing the electricity lines the crossingscheme should be designed at the design stage and

take the terrain characteristic along the project lineinto consideration

(6) The material transport plan should take weather andtransportation environment into consideration opti-mize the use of different transportation facilities andmake the fullest use of crawler-transporter vehicleand cableway

6 Conclusions

In this paper a hybrid evaluation model based on AHPand FCE method is implemented to evaluate the risk ofldquoZhejiang-Fuzhourdquo UHV power transmission constructionprojectThis hybrid evaluationmodel takes full advantages ofAHP and FCEmethod After the risk evaluation index systemis built the AHP is used to determine the index weightand FCE method is used to evaluate the project risk Finallythe specific risk control recommendations are proposed Themain results of risk evaluation of ldquoZhejiang-Fuzhourdquo UHVpower transmission construction project are as follows

(1) The risk grade of ldquoZhejiang-Fuzhourdquo UHV powertransmission construction project belongs to ldquomod-eraterdquo which indicates the occurrence probability ofproject risk is medium and the risk occurrence willcause general loss

(2) ldquoSociety riskrdquo has the highest level and the next isldquopolicy and law riskrdquo ldquotechnique riskrdquo ldquonatural envi-ronmental riskrdquo and ldquomanagement riskrdquo respectivelyldquosociety riskrdquo ldquopolicy and law riskrdquo and ldquotechnologyriskrdquo should be paid more attention in the risk man-agement and control for ldquoZhejiang-Fuzhourdquo UHVpower transmission construction project

(3) Risk control recommendations for main risk criteriawhich include society risk policy and law risk andtechnology risk are proposed

(4) This hybrid evaluation model is feasible and effectivewhich can effectively evaluate the risk of UHV powertransmission construction project

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

This study is supported by the Humanity and Social Scienceproject of the Ministry of Education of China (Project no11YJA790217) and the National Natural Science Foundationof China (Project no 71373076)

References

[1] J P Liu D X Niu and X H Song ldquoThe energy supply anddemand pattern of China a review of evolution and sustainabledevelopmentrdquo Renewable and Sustainable Energy Reviews vol25 pp 220ndash228 2013

14 Mathematical Problems in Engineering

[2] C C Lin C H Yang and J Z Shyua ldquoA comparison ofinnovation policy in the smart grid industry across the pacificchina and the USArdquo Energy Policy vol 57 pp 119ndash132 2013

[3] M Bolinger and R Wiser ldquoA comparative analysis of businessstructures suitable for farmer-ownedwind power projects in theUnited Statesrdquo Energy Policy vol 34 no 14 pp 1750ndash1761 2006

[4] S Grassi N Chokani and R S Abhari ldquoLarge scale technicaland economical assessment of wind energy potential with a GIStool case study Iowardquo Energy Policy vol 45 pp 73ndash85 2012

[5] MHellstrom I Ruuska KWikstrom andD Jafs ldquoProject gov-ernance and path creation in the early stages of Finnish nuclearpower projectsrdquo International Journal of Project Managementvol 31 no 5 pp 712ndash723 2013

[6] P Baumann and G Stevanella ldquoFish passage principles to beconsidered for medium and large dams the case study of afish passage concept for a hydroelectric power project on theMekong mainstem in Laosrdquo Ecological Engineering vol 48 pp79ndash85 2012

[7] W Amatayakul and G Berndes ldquoDetermining factor for thedevelopment of CDM biomass power projectsrdquo Energy forSustainable Development vol 16 pp 197ndash203 2012

[8] J L Liu Q X Li and Y H Wang ldquoRisk analysis in ultradeep scientific drilling project-A fuzzy synthetic evaluationapproachrdquo International Journal of Project Management vol 31no 3 pp 449ndash458 2013

[9] A Badri S Nadeau and A Gbodossou ldquoA new practicalapproach to risk management for underground mining projectin Quebecrdquo Journal of Loss Prevention in the Process Industriesvol 26 no 6 pp 1145ndash1158 2013

[10] J B Song D R Song X Q Zhang and Y Sun ldquoRiskidentification for PPP waste-to-energy incineration projects inChinardquo Energy Policy vol 61 pp 953ndash962 2013

[11] Y Hu J F Du X Z Zhang et al ldquoAn integrative frameworkfor intelligent software project risk planningrdquo Decision SupportSystems vol 55 no 4 pp 927ndash937 2013

[12] T L Saaty The Analytic Hierarchy Process McGraw-Hill NewYork NY USA 1980

[13] M P Amiri ldquoProject selection for oil-fields development byusing the AHP and fuzzy TOPSIS methodsrdquo Expert Systemswith Applications vol 37 no 9 pp 6218ndash6224 2010

[14] H Z Li and S Guo ldquoExternal economies evaluation of windpower engineering project based on analytic hierarchy processand matter-element extension modelrdquo Mathematical Problemsin Engineering vol 2013 Article ID 848901 11 pages 2013

[15] F-G Chen H-L Yao andW-G Shi ldquoApplication of fuzzy andsynthetic judgment to risk assessment of dammed lakerdquo Journalof Shanghai Jiaotong University vol 45 no 1 pp 67ndash75 2011

[16] K Fang B-F He M Yang and Z-C Wang ldquoApplication offuzzy comprehensive evaluation method to CENSrdquo Journal ofHarbin Institute of Technology vol 43 no 5 pp 30ndash36 2011

Submit your manuscripts athttpwwwhindawicom

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mathematical Problems in Engineering

Hindawi Publishing Corporationhttpwwwhindawicom

Differential EquationsInternational Journal of

Volume 2014

Applied MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mathematical PhysicsAdvances in

Complex AnalysisJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

OptimizationJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Operations ResearchAdvances in

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Function Spaces

Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of Mathematics and Mathematical Sciences

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Algebra

Discrete Dynamics in Nature and Society

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Decision SciencesAdvances in

Discrete MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom

Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Stochastic AnalysisInternational Journal of

14 Mathematical Problems in Engineering

[2] C C Lin C H Yang and J Z Shyua ldquoA comparison ofinnovation policy in the smart grid industry across the pacificchina and the USArdquo Energy Policy vol 57 pp 119ndash132 2013

[3] M Bolinger and R Wiser ldquoA comparative analysis of businessstructures suitable for farmer-ownedwind power projects in theUnited Statesrdquo Energy Policy vol 34 no 14 pp 1750ndash1761 2006

[4] S Grassi N Chokani and R S Abhari ldquoLarge scale technicaland economical assessment of wind energy potential with a GIStool case study Iowardquo Energy Policy vol 45 pp 73ndash85 2012

[5] MHellstrom I Ruuska KWikstrom andD Jafs ldquoProject gov-ernance and path creation in the early stages of Finnish nuclearpower projectsrdquo International Journal of Project Managementvol 31 no 5 pp 712ndash723 2013

[6] P Baumann and G Stevanella ldquoFish passage principles to beconsidered for medium and large dams the case study of afish passage concept for a hydroelectric power project on theMekong mainstem in Laosrdquo Ecological Engineering vol 48 pp79ndash85 2012

[7] W Amatayakul and G Berndes ldquoDetermining factor for thedevelopment of CDM biomass power projectsrdquo Energy forSustainable Development vol 16 pp 197ndash203 2012

[8] J L Liu Q X Li and Y H Wang ldquoRisk analysis in ultradeep scientific drilling project-A fuzzy synthetic evaluationapproachrdquo International Journal of Project Management vol 31no 3 pp 449ndash458 2013

[9] A Badri S Nadeau and A Gbodossou ldquoA new practicalapproach to risk management for underground mining projectin Quebecrdquo Journal of Loss Prevention in the Process Industriesvol 26 no 6 pp 1145ndash1158 2013

[10] J B Song D R Song X Q Zhang and Y Sun ldquoRiskidentification for PPP waste-to-energy incineration projects inChinardquo Energy Policy vol 61 pp 953ndash962 2013

[11] Y Hu J F Du X Z Zhang et al ldquoAn integrative frameworkfor intelligent software project risk planningrdquo Decision SupportSystems vol 55 no 4 pp 927ndash937 2013

[12] T L Saaty The Analytic Hierarchy Process McGraw-Hill NewYork NY USA 1980

[13] M P Amiri ldquoProject selection for oil-fields development byusing the AHP and fuzzy TOPSIS methodsrdquo Expert Systemswith Applications vol 37 no 9 pp 6218ndash6224 2010

[14] H Z Li and S Guo ldquoExternal economies evaluation of windpower engineering project based on analytic hierarchy processand matter-element extension modelrdquo Mathematical Problemsin Engineering vol 2013 Article ID 848901 11 pages 2013

[15] F-G Chen H-L Yao andW-G Shi ldquoApplication of fuzzy andsynthetic judgment to risk assessment of dammed lakerdquo Journalof Shanghai Jiaotong University vol 45 no 1 pp 67ndash75 2011

[16] K Fang B-F He M Yang and Z-C Wang ldquoApplication offuzzy comprehensive evaluation method to CENSrdquo Journal ofHarbin Institute of Technology vol 43 no 5 pp 30ndash36 2011

Submit your manuscripts athttpwwwhindawicom

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mathematical Problems in Engineering

Hindawi Publishing Corporationhttpwwwhindawicom

Differential EquationsInternational Journal of

Volume 2014

Applied MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mathematical PhysicsAdvances in

Complex AnalysisJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

OptimizationJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Operations ResearchAdvances in

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Function Spaces

Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of Mathematics and Mathematical Sciences

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Algebra

Discrete Dynamics in Nature and Society

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Decision SciencesAdvances in

Discrete MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom

Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Stochastic AnalysisInternational Journal of

Submit your manuscripts athttpwwwhindawicom

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mathematical Problems in Engineering

Hindawi Publishing Corporationhttpwwwhindawicom

Differential EquationsInternational Journal of

Volume 2014

Applied MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Mathematical PhysicsAdvances in

Complex AnalysisJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

OptimizationJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Operations ResearchAdvances in

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Function Spaces

Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of Mathematics and Mathematical Sciences

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Algebra

Discrete Dynamics in Nature and Society

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Decision SciencesAdvances in

Discrete MathematicsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom

Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Stochastic AnalysisInternational Journal of